Overview

Dataset statistics

Number of variables113
Number of observations319952
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory275.8 MiB
Average record size in memory904.0 B

Variable types

Numeric6
Categorical92
Text14
Unsupported1

Alerts

NPCFP1 is highly imbalanced (76.8%)Imbalance
NPCFP3 is highly imbalanced (86.4%)Imbalance
NPCFP4B is highly imbalanced (67.4%)Imbalance
NPCFP4C is highly imbalanced (54.8%)Imbalance
NPCFP4D is highly imbalanced (73.3%)Imbalance
NPCFP8A is highly imbalanced (62.0%)Imbalance
NPCFP8B is highly imbalanced (61.7%)Imbalance
NPCFP10A is highly imbalanced (96.9%)Imbalance
NPCFP10B is highly imbalanced (74.3%)Imbalance
NPCFP10C is highly imbalanced (83.9%)Imbalance
NPCFP10D is highly imbalanced (88.9%)Imbalance
NPCFP10E is highly imbalanced (59.3%)Imbalance
NPCFP11A is highly imbalanced (79.5%)Imbalance
NPCFP13D is highly imbalanced (86.1%)Imbalance
NPCFP14A is highly imbalanced (54.3%)Imbalance
NPCFP14B is highly imbalanced (79.3%)Imbalance
NPCFP14C is highly imbalanced (90.5%)Imbalance
NPCFP14D is highly imbalanced (70.3%)Imbalance
NPCFP14E is highly imbalanced (66.2%)Imbalance
NPCFP14F is highly imbalanced (80.5%)Imbalance
NPCFP14G is highly imbalanced (91.4%)Imbalance
NPCFP14H is highly imbalanced (91.4%)Imbalance
NPCFP14I is highly imbalanced (88.9%)Imbalance
NPCFP14J is highly imbalanced (89.0%)Imbalance
NPCFP14K is highly imbalanced (96.2%)Imbalance
NPCFP14L is highly imbalanced (95.7%)Imbalance
NPCFP15 is highly imbalanced (50.2%)Imbalance
NPCFP16 is highly imbalanced (77.4%)Imbalance
NPCFP19 is highly imbalanced (91.1%)Imbalance
NPCFP20 is highly imbalanced (91.3%)Imbalance
NPCFP21A is highly imbalanced (83.9%)Imbalance
NPCFP21B is highly imbalanced (92.7%)Imbalance
NPCFP21C is highly imbalanced (88.8%)Imbalance
NPCFP21D is highly imbalanced (94.7%)Imbalance
NPCFP21E is highly imbalanced (95.8%)Imbalance
NPCFP21F is highly imbalanced (94.4%)Imbalance
NPCFP21G is highly imbalanced (95.7%)Imbalance
NPCFP21H is highly imbalanced (95.1%)Imbalance
NPCFP21I is highly imbalanced (72.4%)Imbalance
NPCFP22 is highly imbalanced (79.9%)Imbalance
NPCFP23 is highly imbalanced (82.7%)Imbalance
NPCFP24 is highly imbalanced (87.1%)Imbalance
NPCFP24A is highly imbalanced (94.3%)Imbalance
NPCFP24B is highly imbalanced (98.3%)Imbalance
NPCFP24C is highly imbalanced (98.9%)Imbalance
NPCFP25A is highly imbalanced (99.5%)Imbalance
NPCFP25B is highly imbalanced (98.9%)Imbalance
NPCFP25C is highly imbalanced (99.4%)Imbalance
NPCFP25E is highly imbalanced (> 99.9%)Imbalance
NPCFP25F is highly imbalanced (99.9%)Imbalance
NPCFP26 is highly imbalanced (69.9%)Imbalance
NPCFP26A is highly imbalanced (90.1%)Imbalance
NPCFP29 is highly imbalanced (85.4%)Imbalance
NPCFP30 is highly imbalanced (70.5%)Imbalance
NPCFP31 is highly imbalanced (80.2%)Imbalance
NPCFP32 is highly imbalanced (84.9%)Imbalance
NPCFP33B is highly imbalanced (52.9%)Imbalance
NPCFP33C is highly imbalanced (60.4%)Imbalance
NPCFP33D is highly imbalanced (79.7%)Imbalance
NPCFP33E is highly imbalanced (65.8%)Imbalance
NPCFP33F is highly imbalanced (91.7%)Imbalance
NPCFP35A is highly imbalanced (57.9%)Imbalance
NPCFP35B is highly imbalanced (81.4%)Imbalance
NPCFP39 is highly imbalanced (73.4%)Imbalance
NPCFP39A is highly imbalanced (92.7%)Imbalance
NPCFP41 is highly imbalanced (67.7%)Imbalance
NPCFP42 is highly imbalanced (94.4%)Imbalance
NPCFP43 is highly imbalanced (61.9%)Imbalance
NPCFP43A is highly imbalanced (78.1%)Imbalance
NPCFP34 is highly skewed (γ1 = 24.43056843)Skewed
DIRECTORIO_PER has unique valuesUnique
FEX_C is an unsupported type, check if it needs cleaning or further analysisUnsupported
NPCFP34 has 243848 (76.2%) zerosZeros

Reproduction

Analysis started2024-05-07 04:58:09.463028
Analysis finished2024-05-07 04:59:07.610407
Duration58.15 seconds
Software versionydata-profiling vv4.6.5
Download configurationconfig.json

Variables

DIRECTORIO_PER
Real number (ℝ)

UNIQUE 

Distinct319952
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19682295
Minimum10100011
Maximum3.1754311 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:07.713798image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum10100011
5-th percentile10913314
Q114570212
median18186114
Q324850312
95-th percentile29416912
Maximum3.1754311 × 108
Range3.074431 × 108
Interquartile range (IQR)10280100

Descriptive statistics

Standard deviation7563170.8
Coefficient of variation (CV)0.38426264
Kurtosis290.38191
Mean19682295
Median Absolute Deviation (MAD)4765449.5
Skewness10.43723
Sum6.2973897 × 1012
Variance5.7201552 × 1013
MonotonicityNot monotonic
2024-05-06T23:59:07.865984image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10100011 1
 
< 0.1%
23193513 1
 
< 0.1%
23194413 1
 
< 0.1%
23194412 1
 
< 0.1%
23194411 1
 
< 0.1%
23193714 1
 
< 0.1%
23193713 1
 
< 0.1%
23193712 1
 
< 0.1%
23193711 1
 
< 0.1%
23193512 1
 
< 0.1%
Other values (319942) 319942
> 99.9%
ValueCountFrequency (%)
10100011 1
< 0.1%
10100012 1
< 0.1%
10100013 1
< 0.1%
10100111 1
< 0.1%
10100112 1
< 0.1%
10100113 1
< 0.1%
10100114 1
< 0.1%
10100211 1
< 0.1%
10100212 1
< 0.1%
10100311 1
< 0.1%
ValueCountFrequency (%)
317543112 1
< 0.1%
317543111 1
< 0.1%
317543110 1
< 0.1%
317463110 1
< 0.1%
315231110 1
< 0.1%
315230110 1
< 0.1%
294700110 1
< 0.1%
291262110 1
< 0.1%
287404110 1
< 0.1%
281937110 1
< 0.1%

DIRECTORIO_HOG
Real number (ℝ)

Distinct109111
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1955277.1
Minimum1010001
Maximum3178851
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:08.012131image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1010001
5-th percentile1091276.5
Q11456781
median1818101
Q32483603.5
95-th percentile2940691
Maximum3178851
Range2168850
Interquartile range (IQR)1026822.5

Descriptive statistics

Standard deviation586867.83
Coefficient of variation (CV)0.30014561
Kurtosis-1.1519761
Mean1955277.1
Median Absolute Deviation (MAD)475920
Skewness0.26116389
Sum6.2559481 × 1011
Variance3.4441385 × 1011
MonotonicityIncreasing
2024-05-06T23:59:08.147699image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1409051 17
 
< 0.1%
1091071 14
 
< 0.1%
1857011 14
 
< 0.1%
1692321 14
 
< 0.1%
1590861 14
 
< 0.1%
1120141 13
 
< 0.1%
2803081 13
 
< 0.1%
1473411 13
 
< 0.1%
1294831 13
 
< 0.1%
1353501 13
 
< 0.1%
Other values (109101) 319814
> 99.9%
ValueCountFrequency (%)
1010001 3
< 0.1%
1010011 4
< 0.1%
1010021 2
 
< 0.1%
1010031 3
< 0.1%
1010041 1
 
< 0.1%
1010051 1
 
< 0.1%
1010061 1
 
< 0.1%
1010071 4
< 0.1%
1010081 5
< 0.1%
1010082 3
< 0.1%
ValueCountFrequency (%)
3178851 2
 
< 0.1%
3178811 2
 
< 0.1%
3178741 1
 
< 0.1%
3178591 1
 
< 0.1%
3178441 2
 
< 0.1%
3178351 4
< 0.1%
3178341 2
 
< 0.1%
3178321 2
 
< 0.1%
3178311 3
< 0.1%
3178251 5
< 0.1%

DIRECTORIO
Real number (ℝ)

Distinct107218
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean195527.6
Minimum101000
Maximum317885
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:08.295856image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum101000
5-th percentile109127.55
Q1145678
median181810
Q3248360.25
95-th percentile294069
Maximum317885
Range216885
Interquartile range (IQR)102682.25

Descriptive statistics

Standard deviation58686.783
Coefficient of variation (CV)0.30014577
Kurtosis-1.1519761
Mean195527.6
Median Absolute Deviation (MAD)47592
Skewness0.26116388
Sum6.2559448 × 1010
Variance3.4441385 × 109
MonotonicityIncreasing
2024-05-06T23:59:08.442844image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
184980 22
 
< 0.1%
145788 22
 
< 0.1%
112379 21
 
< 0.1%
172991 19
 
< 0.1%
135993 19
 
< 0.1%
145803 18
 
< 0.1%
140905 17
 
< 0.1%
111041 17
 
< 0.1%
104460 16
 
< 0.1%
112477 16
 
< 0.1%
Other values (107208) 319765
99.9%
ValueCountFrequency (%)
101000 3
 
< 0.1%
101001 4
< 0.1%
101002 2
 
< 0.1%
101003 3
 
< 0.1%
101004 1
 
< 0.1%
101005 1
 
< 0.1%
101006 1
 
< 0.1%
101007 4
< 0.1%
101008 8
< 0.1%
101009 5
< 0.1%
ValueCountFrequency (%)
317885 2
 
< 0.1%
317881 2
 
< 0.1%
317874 1
 
< 0.1%
317859 1
 
< 0.1%
317844 2
 
< 0.1%
317835 4
< 0.1%
317834 2
 
< 0.1%
317832 2
 
< 0.1%
317831 3
< 0.1%
317825 5
< 0.1%

SECUENCIA_P
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0194842
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:08.556225image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.17583773
Coefficient of variation (CV)0.17247716
Kurtosis199.18062
Mean1.0194842
Median Absolute Deviation (MAD)0
Skewness12.069991
Sum326186
Variance0.030918908
MonotonicityNot monotonic
2024-05-06T23:59:08.668238image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 315132
98.5%
2 3754
 
1.2%
3 805
 
0.3%
4 199
 
0.1%
5 48
 
< 0.1%
6 7
 
< 0.1%
7 4
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
1 315132
98.5%
2 3754
 
1.2%
3 805
 
0.3%
4 199
 
0.1%
5 48
 
< 0.1%
6 7
 
< 0.1%
7 4
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
8 2
 
< 0.1%
7 4
 
< 0.1%
6 7
 
< 0.1%
5 48
 
< 0.1%
4 199
 
0.1%
3 805
 
0.3%
2 3754
 
1.2%
1 315132
98.5%

ORDEN
Real number (ℝ)

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.333525
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:08.780381image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum17
Range16
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3719547
Coefficient of variation (CV)0.58793229
Kurtosis2.4552737
Mean2.333525
Median Absolute Deviation (MAD)1
Skewness1.2729511
Sum746616
Variance1.8822597
MonotonicityNot monotonic
2024-05-06T23:59:08.894635image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1 109111
34.1%
2 90132
28.2%
3 62482
19.5%
4 35646
 
11.1%
5 14103
 
4.4%
6 5101
 
1.6%
7 1980
 
0.6%
8 801
 
0.3%
9 339
 
0.1%
10 142
 
< 0.1%
Other values (7) 115
 
< 0.1%
ValueCountFrequency (%)
1 109111
34.1%
2 90132
28.2%
3 62482
19.5%
4 35646
 
11.1%
5 14103
 
4.4%
6 5101
 
1.6%
7 1980
 
0.6%
8 801
 
0.3%
9 339
 
0.1%
10 142
 
< 0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
16 1
 
< 0.1%
15 1
 
< 0.1%
14 5
 
< 0.1%
13 13
 
< 0.1%
12 30
 
< 0.1%
11 64
 
< 0.1%
10 142
 
< 0.1%
9 339
0.1%
8 801
0.3%

NPCFP1
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
1
300326 
2
 
17066
9
 
2560

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 300326
93.9%
2 17066
 
5.3%
9 2560
 
0.8%

Length

2024-05-06T23:59:09.015129image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:09.114568image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 300326
93.9%
2 17066
 
5.3%
9 2560
 
0.8%

Most occurring characters

ValueCountFrequency (%)
1 300326
93.9%
2 17066
 
5.3%
9 2560
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 300326
93.9%
2 17066
 
5.3%
9 2560
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 300326
93.9%
2 17066
 
5.3%
9 2560
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 300326
93.9%
2 17066
 
5.3%
9 2560
 
0.8%

NPCFP2
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
1
215468 
3
74807 
 
19626
2
 
7908
9
 
2143

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 215468
67.3%
3 74807
 
23.4%
19626
 
6.1%
2 7908
 
2.5%
9 2143
 
0.7%

Length

2024-05-06T23:59:09.224328image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:09.339923image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 215468
71.7%
3 74807
 
24.9%
2 7908
 
2.6%
9 2143
 
0.7%

Most occurring characters

ValueCountFrequency (%)
1 215468
67.3%
3 74807
 
23.4%
19626
 
6.1%
2 7908
 
2.5%
9 2143
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 300326
93.9%
Space Separator 19626
 
6.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 215468
71.7%
3 74807
 
24.9%
2 7908
 
2.6%
9 2143
 
0.7%
Space Separator
ValueCountFrequency (%)
19626
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 215468
67.3%
3 74807
 
23.4%
19626
 
6.1%
2 7908
 
2.5%
9 2143
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 215468
67.3%
3 74807
 
23.4%
19626
 
6.1%
2 7908
 
2.5%
9 2143
 
0.7%

NPCFP3
Categorical

IMBALANCE 

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
302886 
5
 
4251
1
 
3528
6
 
2588
8
 
2313
Other values (5)
 
4386

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
302886
94.7%
5 4251
 
1.3%
1 3528
 
1.1%
6 2588
 
0.8%
8 2313
 
0.7%
3 1565
 
0.5%
9 984
 
0.3%
2 959
 
0.3%
7 605
 
0.2%
4 273
 
0.1%

Length

2024-05-06T23:59:09.463637image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:09.585962image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
5 4251
24.9%
1 3528
20.7%
6 2588
15.2%
8 2313
13.6%
3 1565
 
9.2%
9 984
 
5.8%
2 959
 
5.6%
7 605
 
3.5%
4 273
 
1.6%

Most occurring characters

ValueCountFrequency (%)
302886
94.7%
5 4251
 
1.3%
1 3528
 
1.1%
6 2588
 
0.8%
8 2313
 
0.7%
3 1565
 
0.5%
9 984
 
0.3%
2 959
 
0.3%
7 605
 
0.2%
4 273
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 302886
94.7%
Decimal Number 17066
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4251
24.9%
1 3528
20.7%
6 2588
15.2%
8 2313
13.6%
3 1565
 
9.2%
9 984
 
5.8%
2 959
 
5.6%
7 605
 
3.5%
4 273
 
1.6%
Space Separator
ValueCountFrequency (%)
302886
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
302886
94.7%
5 4251
 
1.3%
1 3528
 
1.1%
6 2588
 
0.8%
8 2313
 
0.7%
3 1565
 
0.5%
9 984
 
0.3%
2 959
 
0.3%
7 605
 
0.2%
4 273
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
302886
94.7%
5 4251
 
1.3%
1 3528
 
1.1%
6 2588
 
0.8%
8 2313
 
0.7%
3 1565
 
0.5%
9 984
 
0.3%
2 959
 
0.3%
7 605
 
0.2%
4 273
 
0.1%

NPCFP4A
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
260528 
1
59424 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row1
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
260528
81.4%
1 59424
 
18.6%

Length

2024-05-06T23:59:09.717035image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:09.813397image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 59424
100.0%

Most occurring characters

ValueCountFrequency (%)
260528
81.4%
1 59424
 
18.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 260528
81.4%
Decimal Number 59424
 
18.6%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
260528
100.0%
Decimal Number
ValueCountFrequency (%)
1 59424
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
260528
81.4%
1 59424
 
18.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
260528
81.4%
1 59424
 
18.6%

NPCFP4B
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
300889 
1
 
19063

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
300889
94.0%
1 19063
 
6.0%

Length

2024-05-06T23:59:09.921360image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:10.018074image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 19063
100.0%

Most occurring characters

ValueCountFrequency (%)
300889
94.0%
1 19063
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Space Separator 300889
94.0%
Decimal Number 19063
 
6.0%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
300889
100.0%
Decimal Number
ValueCountFrequency (%)
1 19063
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
300889
94.0%
1 19063
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
300889
94.0%
1 19063
 
6.0%

NPCFP4C
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
289659 
1
30293 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row1
5th row

Common Values

ValueCountFrequency (%)
289659
90.5%
1 30293
 
9.5%

Length

2024-05-06T23:59:10.118500image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:10.215572image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 30293
100.0%

Most occurring characters

ValueCountFrequency (%)
289659
90.5%
1 30293
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 289659
90.5%
Decimal Number 30293
 
9.5%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
289659
100.0%
Decimal Number
ValueCountFrequency (%)
1 30293
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
289659
90.5%
1 30293
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
289659
90.5%
1 30293
 
9.5%

NPCFP4D
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
305365 
1
 
14587

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row1
4th row
5th row

Common Values

ValueCountFrequency (%)
305365
95.4%
1 14587
 
4.6%

Length

2024-05-06T23:59:10.320580image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:10.418738image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 14587
100.0%

Most occurring characters

ValueCountFrequency (%)
305365
95.4%
1 14587
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 305365
95.4%
Decimal Number 14587
 
4.6%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
305365
100.0%
Decimal Number
ValueCountFrequency (%)
1 14587
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
305365
95.4%
1 14587
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
305365
95.4%
1 14587
 
4.6%

NPCFP4E
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
219663 
1
100289 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row
3rd row
4th row
5th row1

Common Values

ValueCountFrequency (%)
219663
68.7%
1 100289
31.3%

Length

2024-05-06T23:59:10.523523image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:10.614917image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 100289
100.0%

Most occurring characters

ValueCountFrequency (%)
219663
68.7%
1 100289
31.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 219663
68.7%
Decimal Number 100289
31.3%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
219663
100.0%
Decimal Number
ValueCountFrequency (%)
1 100289
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
219663
68.7%
1 100289
31.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
219663
68.7%
1 100289
31.3%

NPCFP5
Text

Distinct2755
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:10.892712image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length2.4527835
Min length1

Characters and Unicode

Total characters784773
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1586 ?
Unique (%)0.5%

Sample

1st row
2nd row80000
3rd row
4th row210000
5th row
ValueCountFrequency (%)
80000 4507
 
4.2%
90000 4021
 
3.7%
99 4009
 
3.7%
100000 3427
 
3.2%
120000 3395
 
3.1%
30000 3212
 
3.0%
92000 2954
 
2.7%
200000 2914
 
2.7%
60000 2858
 
2.6%
40000 2609
 
2.4%
Other values (2744) 74594
68.8%
2024-05-06T23:59:11.352127image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 369664
47.1%
211452
26.9%
2 37680
 
4.8%
9 30605
 
3.9%
1 28936
 
3.7%
5 22847
 
2.9%
8 22116
 
2.8%
3 21861
 
2.8%
4 17040
 
2.2%
6 13310
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 573321
73.1%
Space Separator 211452
 
26.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 369664
64.5%
2 37680
 
6.6%
9 30605
 
5.3%
1 28936
 
5.0%
5 22847
 
4.0%
8 22116
 
3.9%
3 21861
 
3.8%
4 17040
 
3.0%
6 13310
 
2.3%
7 9262
 
1.6%
Space Separator
ValueCountFrequency (%)
211452
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 784773
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 369664
47.1%
211452
26.9%
2 37680
 
4.8%
9 30605
 
3.9%
1 28936
 
3.7%
5 22847
 
2.9%
8 22116
 
2.8%
3 21861
 
2.8%
4 17040
 
2.2%
6 13310
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 784773
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 369664
47.1%
211452
26.9%
2 37680
 
4.8%
9 30605
 
3.9%
1 28936
 
3.7%
5 22847
 
2.9%
8 22116
 
2.8%
3 21861
 
2.8%
4 17040
 
2.2%
6 13310
 
1.7%

NPCFP7
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
268126 
1
30057 
 
21769

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 268126
83.8%
1 30057
 
9.4%
21769
 
6.8%

Length

2024-05-06T23:59:11.532824image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:11.645329image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 268126
89.9%
1 30057
 
10.1%

Most occurring characters

ValueCountFrequency (%)
2 268126
83.8%
1 30057
 
9.4%
21769
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 298183
93.2%
Space Separator 21769
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 268126
89.9%
1 30057
 
10.1%
Space Separator
ValueCountFrequency (%)
21769
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 268126
83.8%
1 30057
 
9.4%
21769
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 268126
83.8%
1 30057
 
9.4%
21769
 
6.8%

NPCFP8
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
206822 
3
46854 
1
21855 
21769 
4
 
12003
Other values (2)
 
10649

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row3
4th row3
5th row2

Common Values

ValueCountFrequency (%)
2 206822
64.6%
3 46854
 
14.6%
1 21855
 
6.8%
21769
 
6.8%
4 12003
 
3.8%
5 6194
 
1.9%
9 4455
 
1.4%

Length

2024-05-06T23:59:11.750817image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:11.860766image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 206822
69.4%
3 46854
 
15.7%
1 21855
 
7.3%
4 12003
 
4.0%
5 6194
 
2.1%
9 4455
 
1.5%

Most occurring characters

ValueCountFrequency (%)
2 206822
64.6%
3 46854
 
14.6%
1 21855
 
6.8%
21769
 
6.8%
4 12003
 
3.8%
5 6194
 
1.9%
9 4455
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 298183
93.2%
Space Separator 21769
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 206822
69.4%
3 46854
 
15.7%
1 21855
 
7.3%
4 12003
 
4.0%
5 6194
 
2.1%
9 4455
 
1.5%
Space Separator
ValueCountFrequency (%)
21769
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 206822
64.6%
3 46854
 
14.6%
1 21855
 
6.8%
21769
 
6.8%
4 12003
 
3.8%
5 6194
 
1.9%
9 4455
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 206822
64.6%
3 46854
 
14.6%
1 21855
 
6.8%
21769
 
6.8%
4 12003
 
3.8%
5 6194
 
1.9%
9 4455
 
1.4%

NPCFP8A
Categorical

IMBALANCE 

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
254901 
5
33398 
1
 
12979
2
 
9118
6
 
4776
Other values (3)
 
4780

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row5
3rd row5
4th row4
5th row

Common Values

ValueCountFrequency (%)
254901
79.7%
5 33398
 
10.4%
1 12979
 
4.1%
2 9118
 
2.8%
6 4776
 
1.5%
3 2117
 
0.7%
4 1761
 
0.6%
7 902
 
0.3%

Length

2024-05-06T23:59:11.978912image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:12.097561image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
5 33398
51.3%
1 12979
 
20.0%
2 9118
 
14.0%
6 4776
 
7.3%
3 2117
 
3.3%
4 1761
 
2.7%
7 902
 
1.4%

Most occurring characters

ValueCountFrequency (%)
254901
79.7%
5 33398
 
10.4%
1 12979
 
4.1%
2 9118
 
2.8%
6 4776
 
1.5%
3 2117
 
0.7%
4 1761
 
0.6%
7 902
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 254901
79.7%
Decimal Number 65051
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 33398
51.3%
1 12979
 
20.0%
2 9118
 
14.0%
6 4776
 
7.3%
3 2117
 
3.3%
4 1761
 
2.7%
7 902
 
1.4%
Space Separator
ValueCountFrequency (%)
254901
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
254901
79.7%
5 33398
 
10.4%
1 12979
 
4.1%
2 9118
 
2.8%
6 4776
 
1.5%
3 2117
 
0.7%
4 1761
 
0.6%
7 902
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
254901
79.7%
5 33398
 
10.4%
1 12979
 
4.1%
2 9118
 
2.8%
6 4776
 
1.5%
3 2117
 
0.7%
4 1761
 
0.6%
7 902
 
0.3%

NPCFP8B
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
284621 
 
21769
1
 
13562

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 284621
89.0%
21769
 
6.8%
1 13562
 
4.2%

Length

2024-05-06T23:59:12.218857image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:12.317861image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 284621
95.5%
1 13562
 
4.5%

Most occurring characters

ValueCountFrequency (%)
2 284621
89.0%
21769
 
6.8%
1 13562
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 298183
93.2%
Space Separator 21769
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 284621
95.5%
1 13562
 
4.5%
Space Separator
ValueCountFrequency (%)
21769
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 284621
89.0%
21769
 
6.8%
1 13562
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 284621
89.0%
21769
 
6.8%
1 13562
 
4.2%

NPCFP9
Text

Distinct152
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:12.699987image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.9235417
Min length1

Characters and Unicode

Total characters615441
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)< 0.1%

Sample

1st row30
2nd row60
3rd row60
4th row80
5th row40
ValueCountFrequency (%)
30 66639
22.3%
20 39089
13.1%
60 31723
10.6%
15 30584
10.3%
40 25877
 
8.7%
10 22836
 
7.7%
45 17864
 
6.0%
25 8598
 
2.9%
5 8541
 
2.9%
90 8009
 
2.7%
Other values (141) 38423
12.9%
2024-05-06T23:59:13.053785image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 211557
34.4%
5 79855
 
13.0%
3 77598
 
12.6%
1 66063
 
10.7%
2 58856
 
9.6%
4 46686
 
7.6%
6 34851
 
5.7%
21769
 
3.5%
9 11563
 
1.9%
8 3649
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 593672
96.5%
Space Separator 21769
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 211557
35.6%
5 79855
 
13.5%
3 77598
 
13.1%
1 66063
 
11.1%
2 58856
 
9.9%
4 46686
 
7.9%
6 34851
 
5.9%
9 11563
 
1.9%
8 3649
 
0.6%
7 2994
 
0.5%
Space Separator
ValueCountFrequency (%)
21769
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 615441
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 211557
34.4%
5 79855
 
13.0%
3 77598
 
12.6%
1 66063
 
10.7%
2 58856
 
9.6%
4 46686
 
7.6%
6 34851
 
5.7%
21769
 
3.5%
9 11563
 
1.9%
8 3649
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 615441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 211557
34.4%
5 79855
 
13.0%
3 77598
 
12.6%
1 66063
 
10.7%
2 58856
 
9.6%
4 46686
 
7.6%
6 34851
 
5.7%
21769
 
3.5%
9 11563
 
1.9%
8 3649
 
0.6%

NPCFP10A
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
318938 
1
 
1014

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
318938
99.7%
1 1014
 
0.3%

Length

2024-05-06T23:59:13.203971image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:13.299126image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 1014
100.0%

Most occurring characters

ValueCountFrequency (%)
318938
99.7%
1 1014
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 318938
99.7%
Decimal Number 1014
 
0.3%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
318938
100.0%
Decimal Number
ValueCountFrequency (%)
1 1014
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
318938
99.7%
1 1014
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
318938
99.7%
1 1014
 
0.3%

NPCFP10B
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
306083 
1
 
13869

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
306083
95.7%
1 13869
 
4.3%

Length

2024-05-06T23:59:13.402918image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:13.502644image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 13869
100.0%

Most occurring characters

ValueCountFrequency (%)
306083
95.7%
1 13869
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 306083
95.7%
Decimal Number 13869
 
4.3%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
306083
100.0%
Decimal Number
ValueCountFrequency (%)
1 13869
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
306083
95.7%
1 13869
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
306083
95.7%
1 13869
 
4.3%

NPCFP10C
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
312432 
1
 
7520

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row1
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
312432
97.6%
1 7520
 
2.4%

Length

2024-05-06T23:59:13.611194image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:13.721176image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 7520
100.0%

Most occurring characters

ValueCountFrequency (%)
312432
97.6%
1 7520
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 312432
97.6%
Decimal Number 7520
 
2.4%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
312432
100.0%
Decimal Number
ValueCountFrequency (%)
1 7520
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
312432
97.6%
1 7520
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
312432
97.6%
1 7520
 
2.4%

NPCFP10D
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
315247 
1
 
4705

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
315247
98.5%
1 4705
 
1.5%

Length

2024-05-06T23:59:13.822671image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:13.922129image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 4705
100.0%

Most occurring characters

ValueCountFrequency (%)
315247
98.5%
1 4705
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 315247
98.5%
Decimal Number 4705
 
1.5%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
315247
100.0%
Decimal Number
ValueCountFrequency (%)
1 4705
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
315247
98.5%
1 4705
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
315247
98.5%
1 4705
 
1.5%

NPCFP10E
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
1
293905 
 
26047

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 293905
91.9%
26047
 
8.1%

Length

2024-05-06T23:59:14.032072image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:14.135442image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 293905
100.0%

Most occurring characters

ValueCountFrequency (%)
1 293905
91.9%
26047
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 293905
91.9%
Space Separator 26047
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 293905
100.0%
Space Separator
ValueCountFrequency (%)
26047
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 293905
91.9%
26047
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 293905
91.9%
26047
 
8.1%

NPCFP11
Text

Distinct1036
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:14.385015image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.3423576
Min length1

Characters and Unicode

Total characters429490
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique459 ?
Unique (%)0.1%

Sample

1st row
2nd row135000
3rd row
4th row
5th row
ValueCountFrequency (%)
99 1749
 
6.7%
200000 1205
 
4.6%
98 1044
 
4.0%
300000 903
 
3.5%
250000 878
 
3.4%
100000 738
 
2.8%
5000 730
 
2.8%
150000 723
 
2.8%
10000 678
 
2.6%
120000 616
 
2.4%
Other values (1025) 16783
64.4%
2024-05-06T23:59:14.817657image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
293905
68.4%
0 91144
 
21.2%
1 7910
 
1.8%
2 7547
 
1.8%
5 6654
 
1.5%
9 6024
 
1.4%
3 4493
 
1.0%
8 4419
 
1.0%
4 2560
 
0.6%
7 2524
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 293905
68.4%
Decimal Number 135585
31.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 91144
67.2%
1 7910
 
5.8%
2 7547
 
5.6%
5 6654
 
4.9%
9 6024
 
4.4%
3 4493
 
3.3%
8 4419
 
3.3%
4 2560
 
1.9%
7 2524
 
1.9%
6 2310
 
1.7%
Space Separator
ValueCountFrequency (%)
293905
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 429490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
293905
68.4%
0 91144
 
21.2%
1 7910
 
1.8%
2 7547
 
1.8%
5 6654
 
1.5%
9 6024
 
1.4%
3 4493
 
1.0%
8 4419
 
1.0%
4 2560
 
0.6%
7 2524
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 429490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
293905
68.4%
0 91144
 
21.2%
1 7910
 
1.8%
2 7547
 
1.8%
5 6654
 
1.5%
9 6024
 
1.4%
3 4493
 
1.0%
8 4419
 
1.0%
4 2560
 
0.6%
7 2524
 
0.6%

NPCFP11A
Categorical

IMBALANCE 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
293905 
1
 
21263
4
 
3941
3
 
619
2
 
224

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row1
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
293905
91.9%
1 21263
 
6.6%
4 3941
 
1.2%
3 619
 
0.2%
2 224
 
0.1%

Length

2024-05-06T23:59:14.984947image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:15.085581image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 21263
81.6%
4 3941
 
15.1%
3 619
 
2.4%
2 224
 
0.9%

Most occurring characters

ValueCountFrequency (%)
293905
91.9%
1 21263
 
6.6%
4 3941
 
1.2%
3 619
 
0.2%
2 224
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 293905
91.9%
Decimal Number 26047
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21263
81.6%
4 3941
 
15.1%
3 619
 
2.4%
2 224
 
0.9%
Space Separator
ValueCountFrequency (%)
293905
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
293905
91.9%
1 21263
 
6.6%
4 3941
 
1.2%
3 619
 
0.2%
2 224
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
293905
91.9%
1 21263
 
6.6%
4 3941
 
1.2%
3 619
 
0.2%
2 224
 
0.1%

NPCFP12
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
225693 
1
47129 
3
42738 
4
 
3683
5
 
709

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row3
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 225693
70.5%
1 47129
 
14.7%
3 42738
 
13.4%
4 3683
 
1.2%
5 709
 
0.2%

Length

2024-05-06T23:59:15.192828image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:15.295759image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 225693
70.5%
1 47129
 
14.7%
3 42738
 
13.4%
4 3683
 
1.2%
5 709
 
0.2%

Most occurring characters

ValueCountFrequency (%)
2 225693
70.5%
1 47129
 
14.7%
3 42738
 
13.4%
4 3683
 
1.2%
5 709
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 225693
70.5%
1 47129
 
14.7%
3 42738
 
13.4%
4 3683
 
1.2%
5 709
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 225693
70.5%
1 47129
 
14.7%
3 42738
 
13.4%
4 3683
 
1.2%
5 709
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 225693
70.5%
1 47129
 
14.7%
3 42738
 
13.4%
4 3683
 
1.2%
5 709
 
0.2%

NPCFP13A
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
1
215473 
104479 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row
5th row1

Common Values

ValueCountFrequency (%)
1 215473
67.3%
104479
32.7%

Length

2024-05-06T23:59:15.410493image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:15.513263image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 215473
100.0%

Most occurring characters

ValueCountFrequency (%)
1 215473
67.3%
104479
32.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 215473
67.3%
Space Separator 104479
32.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 215473
100.0%
Space Separator
ValueCountFrequency (%)
104479
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 215473
67.3%
104479
32.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 215473
67.3%
104479
32.7%

NPCFP13B
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
234742 
1
85210 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row1
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
234742
73.4%
1 85210
 
26.6%

Length

2024-05-06T23:59:15.616516image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:15.711704image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 85210
100.0%

Most occurring characters

ValueCountFrequency (%)
234742
73.4%
1 85210
 
26.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 234742
73.4%
Decimal Number 85210
 
26.6%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
234742
100.0%
Decimal Number
ValueCountFrequency (%)
1 85210
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
234742
73.4%
1 85210
 
26.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
234742
73.4%
1 85210
 
26.6%

NPCFP13C
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
199805 
1
120147 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row
5th row

Common Values

ValueCountFrequency (%)
199805
62.4%
1 120147
37.6%

Length

2024-05-06T23:59:15.816421image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:15.910983image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 120147
100.0%

Most occurring characters

ValueCountFrequency (%)
199805
62.4%
1 120147
37.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 199805
62.4%
Decimal Number 120147
37.6%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
199805
100.0%
Decimal Number
ValueCountFrequency (%)
1 120147
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
199805
62.4%
1 120147
37.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
199805
62.4%
1 120147
37.6%

NPCFP13D
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
313700 
1
 
6252

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row1
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
313700
98.0%
1 6252
 
2.0%

Length

2024-05-06T23:59:16.014396image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:16.113660image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 6252
100.0%

Most occurring characters

ValueCountFrequency (%)
313700
98.0%
1 6252
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Space Separator 313700
98.0%
Decimal Number 6252
 
2.0%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
313700
100.0%
Decimal Number
ValueCountFrequency (%)
1 6252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
313700
98.0%
1 6252
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
313700
98.0%
1 6252
 
2.0%

NPCFP13E
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
227633 
1
92319 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row1
5th row

Common Values

ValueCountFrequency (%)
227633
71.1%
1 92319
28.9%

Length

2024-05-06T23:59:16.215101image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:16.311115image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 92319
100.0%

Most occurring characters

ValueCountFrequency (%)
227633
71.1%
1 92319
28.9%

Most occurring categories

ValueCountFrequency (%)
Space Separator 227633
71.1%
Decimal Number 92319
28.9%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
227633
100.0%
Decimal Number
ValueCountFrequency (%)
1 92319
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
227633
71.1%
1 92319
28.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
227633
71.1%
1 92319
28.9%

NPCFP14A
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
289149 
1
30803 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 289149
90.4%
1 30803
 
9.6%

Length

2024-05-06T23:59:16.407849image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:16.505545image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 289149
90.4%
1 30803
 
9.6%

Most occurring characters

ValueCountFrequency (%)
2 289149
90.4%
1 30803
 
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 289149
90.4%
1 30803
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 289149
90.4%
1 30803
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 289149
90.4%
1 30803
 
9.6%

NPCFP14B
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
309564 
1
 
10388

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 309564
96.8%
1 10388
 
3.2%

Length

2024-05-06T23:59:16.611964image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:16.708909image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 309564
96.8%
1 10388
 
3.2%

Most occurring characters

ValueCountFrequency (%)
2 309564
96.8%
1 10388
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 309564
96.8%
1 10388
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 309564
96.8%
1 10388
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 309564
96.8%
1 10388
 
3.2%

NPCFP14C
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
316029 
1
 
3923

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 316029
98.8%
1 3923
 
1.2%

Length

2024-05-06T23:59:16.811470image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:16.905974image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 316029
98.8%
1 3923
 
1.2%

Most occurring characters

ValueCountFrequency (%)
2 316029
98.8%
1 3923
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 316029
98.8%
1 3923
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 316029
98.8%
1 3923
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 316029
98.8%
1 3923
 
1.2%

NPCFP14D
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
303129 
1
 
16823

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 303129
94.7%
1 16823
 
5.3%

Length

2024-05-06T23:59:17.020465image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:17.119412image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 303129
94.7%
1 16823
 
5.3%

Most occurring characters

ValueCountFrequency (%)
2 303129
94.7%
1 16823
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 303129
94.7%
1 16823
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 303129
94.7%
1 16823
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 303129
94.7%
1 16823
 
5.3%

NPCFP14E
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
299917 
1
 
20035

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 299917
93.7%
1 20035
 
6.3%

Length

2024-05-06T23:59:17.224550image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:17.325005image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 299917
93.7%
1 20035
 
6.3%

Most occurring characters

ValueCountFrequency (%)
2 299917
93.7%
1 20035
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 299917
93.7%
1 20035
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 299917
93.7%
1 20035
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 299917
93.7%
1 20035
 
6.3%

NPCFP14F
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
310301 
1
 
9651

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 310301
97.0%
1 9651
 
3.0%

Length

2024-05-06T23:59:17.430054image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:17.530939image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 310301
97.0%
1 9651
 
3.0%

Most occurring characters

ValueCountFrequency (%)
2 310301
97.0%
1 9651
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 310301
97.0%
1 9651
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 310301
97.0%
1 9651
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 310301
97.0%
1 9651
 
3.0%

NPCFP14G
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
316498 
1
 
3454

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 316498
98.9%
1 3454
 
1.1%

Length

2024-05-06T23:59:17.635935image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:17.728621image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 316498
98.9%
1 3454
 
1.1%

Most occurring characters

ValueCountFrequency (%)
2 316498
98.9%
1 3454
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 316498
98.9%
1 3454
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 316498
98.9%
1 3454
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 316498
98.9%
1 3454
 
1.1%

NPCFP14H
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
316480 
1
 
3472

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 316480
98.9%
1 3472
 
1.1%

Length

2024-05-06T23:59:17.829770image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:17.926047image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 316480
98.9%
1 3472
 
1.1%

Most occurring characters

ValueCountFrequency (%)
2 316480
98.9%
1 3472
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 316480
98.9%
1 3472
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 316480
98.9%
1 3472
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 316480
98.9%
1 3472
 
1.1%

NPCFP14I
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
315225 
1
 
4727

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 315225
98.5%
1 4727
 
1.5%

Length

2024-05-06T23:59:18.026292image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:18.122398image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 315225
98.5%
1 4727
 
1.5%

Most occurring characters

ValueCountFrequency (%)
2 315225
98.5%
1 4727
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 315225
98.5%
1 4727
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 315225
98.5%
1 4727
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 315225
98.5%
1 4727
 
1.5%

NPCFP14J
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
315290 
1
 
4662

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 315290
98.5%
1 4662
 
1.5%

Length

2024-05-06T23:59:18.229443image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:18.326792image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 315290
98.5%
1 4662
 
1.5%

Most occurring characters

ValueCountFrequency (%)
2 315290
98.5%
1 4662
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 315290
98.5%
1 4662
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 315290
98.5%
1 4662
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 315290
98.5%
1 4662
 
1.5%

NPCFP14K
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
318640 
1
 
1312

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 318640
99.6%
1 1312
 
0.4%

Length

2024-05-06T23:59:18.431495image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:18.534119image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 318640
99.6%
1 1312
 
0.4%

Most occurring characters

ValueCountFrequency (%)
2 318640
99.6%
1 1312
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 318640
99.6%
1 1312
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 318640
99.6%
1 1312
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 318640
99.6%
1 1312
 
0.4%

NPCFP14L
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
318438 
1
 
1514

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 318438
99.5%
1 1514
 
0.5%

Length

2024-05-06T23:59:18.640800image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:18.741758image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 318438
99.5%
1 1514
 
0.5%

Most occurring characters

ValueCountFrequency (%)
2 318438
99.5%
1 1514
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 318438
99.5%
1 1514
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 318438
99.5%
1 1514
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 318438
99.5%
1 1514
 
0.5%

NPCFP15
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
248166 
1
55141 
3
 
8823
2
 
7822

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
248166
77.6%
1 55141
 
17.2%
3 8823
 
2.8%
2 7822
 
2.4%

Length

2024-05-06T23:59:18.844261image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:18.946914image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 55141
76.8%
3 8823
 
12.3%
2 7822
 
10.9%

Most occurring characters

ValueCountFrequency (%)
248166
77.6%
1 55141
 
17.2%
3 8823
 
2.8%
2 7822
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 248166
77.6%
Decimal Number 71786
 
22.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 55141
76.8%
3 8823
 
12.3%
2 7822
 
10.9%
Space Separator
ValueCountFrequency (%)
248166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
248166
77.6%
1 55141
 
17.2%
3 8823
 
2.8%
2 7822
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
248166
77.6%
1 55141
 
17.2%
3 8823
 
2.8%
2 7822
 
2.4%

NPCFP16
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
308248 
1
 
11704

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 308248
96.3%
1 11704
 
3.7%

Length

2024-05-06T23:59:19.058240image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:19.151092image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 308248
96.3%
1 11704
 
3.7%

Most occurring characters

ValueCountFrequency (%)
2 308248
96.3%
1 11704
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 308248
96.3%
1 11704
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 308248
96.3%
1 11704
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 308248
96.3%
1 11704
 
3.7%

NPCFP18
Text

Distinct61
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:19.252308image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.0056508
Min length1

Characters and Unicode

Total characters321760
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
0 3770
32.2%
2 1634
14.0%
3 1282
 
11.0%
1 1233
 
10.5%
5 581
 
5.0%
8 492
 
4.2%
4 468
 
4.0%
15 429
 
3.7%
30 413
 
3.5%
7 389
 
3.3%
Other values (50) 1013
 
8.7%
2024-05-06T23:59:19.534957image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
308248
95.8%
0 4825
 
1.5%
1 2096
 
0.7%
2 2013
 
0.6%
3 1719
 
0.5%
5 1052
 
0.3%
4 551
 
0.2%
8 510
 
0.2%
7 407
 
0.1%
6 238
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 308248
95.8%
Decimal Number 13512
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4825
35.7%
1 2096
15.5%
2 2013
14.9%
3 1719
 
12.7%
5 1052
 
7.8%
4 551
 
4.1%
8 510
 
3.8%
7 407
 
3.0%
6 238
 
1.8%
9 101
 
0.7%
Space Separator
ValueCountFrequency (%)
308248
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 321760
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
308248
95.8%
0 4825
 
1.5%
1 2096
 
0.7%
2 2013
 
0.6%
3 1719
 
0.5%
5 1052
 
0.3%
4 551
 
0.2%
8 510
 
0.2%
7 407
 
0.1%
6 238
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 321760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
308248
95.8%
0 4825
 
1.5%
1 2096
 
0.7%
2 2013
 
0.6%
3 1719
 
0.5%
5 1052
 
0.3%
4 551
 
0.2%
8 510
 
0.2%
7 407
 
0.1%
6 238
 
0.1%

NPCFP19
Categorical

IMBALANCE 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
308248 
1
 
6603
8
 
1116
2
 
1097
3
 
873
Other values (6)
 
2015

Length

Max length2
Median length1
Mean length1.0012721
Min length1

Characters and Unicode

Total characters320359
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
308248
96.3%
1 6603
 
2.1%
8 1116
 
0.3%
2 1097
 
0.3%
3 873
 
0.3%
5 786
 
0.2%
9 448
 
0.1%
10 407
 
0.1%
4 305
 
0.1%
7 63
 
< 0.1%

Length

2024-05-06T23:59:19.695377image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 6603
56.4%
8 1116
 
9.5%
2 1097
 
9.4%
3 873
 
7.5%
5 786
 
6.7%
9 448
 
3.8%
10 407
 
3.5%
4 305
 
2.6%
7 63
 
0.5%
6 6
 
0.1%

Most occurring characters

ValueCountFrequency (%)
308248
96.2%
1 7010
 
2.2%
8 1116
 
0.3%
2 1097
 
0.3%
3 873
 
0.3%
5 786
 
0.2%
9 448
 
0.1%
0 407
 
0.1%
4 305
 
0.1%
7 63
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 308248
96.2%
Decimal Number 12111
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7010
57.9%
8 1116
 
9.2%
2 1097
 
9.1%
3 873
 
7.2%
5 786
 
6.5%
9 448
 
3.7%
0 407
 
3.4%
4 305
 
2.5%
7 63
 
0.5%
6 6
 
< 0.1%
Space Separator
ValueCountFrequency (%)
308248
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 320359
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
308248
96.2%
1 7010
 
2.2%
8 1116
 
0.3%
2 1097
 
0.3%
3 873
 
0.3%
5 786
 
0.2%
9 448
 
0.1%
0 407
 
0.1%
4 305
 
0.1%
7 63
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 320359
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
308248
96.2%
1 7010
 
2.2%
8 1116
 
0.3%
2 1097
 
0.3%
3 873
 
0.3%
5 786
 
0.2%
9 448
 
0.1%
0 407
 
0.1%
4 305
 
0.1%
7 63
 
< 0.1%

NPCFP20
Categorical

IMBALANCE 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
311074 
2
 
5617
1
 
1439
3
 
1330
4
 
357

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
311074
97.2%
2 5617
 
1.8%
1 1439
 
0.4%
3 1330
 
0.4%
4 357
 
0.1%
5 135
 
< 0.1%

Length

2024-05-06T23:59:20.053375image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:20.162259image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 5617
63.3%
1 1439
 
16.2%
3 1330
 
15.0%
4 357
 
4.0%
5 135
 
1.5%

Most occurring characters

ValueCountFrequency (%)
311074
97.2%
2 5617
 
1.8%
1 1439
 
0.4%
3 1330
 
0.4%
4 357
 
0.1%
5 135
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 311074
97.2%
Decimal Number 8878
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5617
63.3%
1 1439
 
16.2%
3 1330
 
15.0%
4 357
 
4.0%
5 135
 
1.5%
Space Separator
ValueCountFrequency (%)
311074
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
311074
97.2%
2 5617
 
1.8%
1 1439
 
0.4%
3 1330
 
0.4%
4 357
 
0.1%
5 135
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
311074
97.2%
2 5617
 
1.8%
1 1439
 
0.4%
3 1330
 
0.4%
4 357
 
0.1%
5 135
 
< 0.1%

NPCFP21A
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
312442 
1
 
7510

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
312442
97.7%
1 7510
 
2.3%

Length

2024-05-06T23:59:20.279150image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:20.381707image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 7510
100.0%

Most occurring characters

ValueCountFrequency (%)
312442
97.7%
1 7510
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 312442
97.7%
Decimal Number 7510
 
2.3%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
312442
100.0%
Decimal Number
ValueCountFrequency (%)
1 7510
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
312442
97.7%
1 7510
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
312442
97.7%
1 7510
 
2.3%

NPCFP21B
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
317131 
1
 
2821

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
317131
99.1%
1 2821
 
0.9%

Length

2024-05-06T23:59:20.483524image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:20.577232image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 2821
100.0%

Most occurring characters

ValueCountFrequency (%)
317131
99.1%
1 2821
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Space Separator 317131
99.1%
Decimal Number 2821
 
0.9%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
317131
100.0%
Decimal Number
ValueCountFrequency (%)
1 2821
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
317131
99.1%
1 2821
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
317131
99.1%
1 2821
 
0.9%

NPCFP21C
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
315151 
1
 
4801

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
315151
98.5%
1 4801
 
1.5%

Length

2024-05-06T23:59:20.678004image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:20.770236image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 4801
100.0%

Most occurring characters

ValueCountFrequency (%)
315151
98.5%
1 4801
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 315151
98.5%
Decimal Number 4801
 
1.5%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
315151
100.0%
Decimal Number
ValueCountFrequency (%)
1 4801
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
315151
98.5%
1 4801
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
315151
98.5%
1 4801
 
1.5%

NPCFP21D
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
318007 
1
 
1945

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
318007
99.4%
1 1945
 
0.6%

Length

2024-05-06T23:59:20.876945image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:20.972872image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 1945
100.0%

Most occurring characters

ValueCountFrequency (%)
318007
99.4%
1 1945
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 318007
99.4%
Decimal Number 1945
 
0.6%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
318007
100.0%
Decimal Number
ValueCountFrequency (%)
1 1945
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
318007
99.4%
1 1945
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
318007
99.4%
1 1945
 
0.6%

NPCFP21E
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
318480 
1
 
1472

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
318480
99.5%
1 1472
 
0.5%

Length

2024-05-06T23:59:21.076523image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:21.172802image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 1472
100.0%

Most occurring characters

ValueCountFrequency (%)
318480
99.5%
1 1472
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 318480
99.5%
Decimal Number 1472
 
0.5%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
318480
100.0%
Decimal Number
ValueCountFrequency (%)
1 1472
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
318480
99.5%
1 1472
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
318480
99.5%
1 1472
 
0.5%

NPCFP21F
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
317914 
1
 
2038

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
317914
99.4%
1 2038
 
0.6%

Length

2024-05-06T23:59:21.272825image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:21.368877image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 2038
100.0%

Most occurring characters

ValueCountFrequency (%)
317914
99.4%
1 2038
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 317914
99.4%
Decimal Number 2038
 
0.6%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
317914
100.0%
Decimal Number
ValueCountFrequency (%)
1 2038
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
317914
99.4%
1 2038
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
317914
99.4%
1 2038
 
0.6%

NPCFP21G
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
318457 
1
 
1495

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
318457
99.5%
1 1495
 
0.5%

Length

2024-05-06T23:59:21.498825image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:21.598161image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 1495
100.0%

Most occurring characters

ValueCountFrequency (%)
318457
99.5%
1 1495
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 318457
99.5%
Decimal Number 1495
 
0.5%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
318457
100.0%
Decimal Number
ValueCountFrequency (%)
1 1495
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
318457
99.5%
1 1495
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
318457
99.5%
1 1495
 
0.5%

NPCFP21H
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
318206 
1
 
1746

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
318206
99.5%
1 1746
 
0.5%

Length

2024-05-06T23:59:21.704168image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:21.799818image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 1746
100.0%

Most occurring characters

ValueCountFrequency (%)
318206
99.5%
1 1746
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 318206
99.5%
Decimal Number 1746
 
0.5%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
318206
100.0%
Decimal Number
ValueCountFrequency (%)
1 1746
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
318206
99.5%
1 1746
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
318206
99.5%
1 1746
 
0.5%

NPCFP21I
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
1
304705 
 
15247

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 304705
95.2%
15247
 
4.8%

Length

2024-05-06T23:59:21.902399image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:21.999158image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 304705
100.0%

Most occurring characters

ValueCountFrequency (%)
1 304705
95.2%
15247
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 304705
95.2%
Space Separator 15247
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 304705
100.0%
Space Separator
ValueCountFrequency (%)
15247
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 304705
95.2%
15247
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 304705
95.2%
15247
 
4.8%

NPCFP22
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
304705 
1
 
10616
2
 
4631

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
304705
95.2%
1 10616
 
3.3%
2 4631
 
1.4%

Length

2024-05-06T23:59:22.099353image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:22.198073image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 10616
69.6%
2 4631
30.4%

Most occurring characters

ValueCountFrequency (%)
304705
95.2%
1 10616
 
3.3%
2 4631
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 304705
95.2%
Decimal Number 15247
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10616
69.6%
2 4631
30.4%
Space Separator
ValueCountFrequency (%)
304705
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
304705
95.2%
1 10616
 
3.3%
2 4631
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
304705
95.2%
1 10616
 
3.3%
2 4631
 
1.4%

NPCFP23
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
304705 
2
 
8060
1
 
3790
3
 
3397

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
304705
95.2%
2 8060
 
2.5%
1 3790
 
1.2%
3 3397
 
1.1%

Length

2024-05-06T23:59:22.303587image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:22.405996image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 8060
52.9%
1 3790
24.9%
3 3397
22.3%

Most occurring characters

ValueCountFrequency (%)
304705
95.2%
2 8060
 
2.5%
1 3790
 
1.2%
3 3397
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 304705
95.2%
Decimal Number 15247
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 8060
52.9%
1 3790
24.9%
3 3397
22.3%
Space Separator
ValueCountFrequency (%)
304705
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
304705
95.2%
2 8060
 
2.5%
1 3790
 
1.2%
3 3397
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
304705
95.2%
2 8060
 
2.5%
1 3790
 
1.2%
3 3397
 
1.1%

NPCFP24
Categorical

IMBALANCE 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
304705 
1
 
7439
5
 
4855
6
 
1554
2
 
822
Other values (2)
 
577

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
304705
95.2%
1 7439
 
2.3%
5 4855
 
1.5%
6 1554
 
0.5%
2 822
 
0.3%
3 501
 
0.2%
4 76
 
< 0.1%

Length

2024-05-06T23:59:22.513612image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:22.621854image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 7439
48.8%
5 4855
31.8%
6 1554
 
10.2%
2 822
 
5.4%
3 501
 
3.3%
4 76
 
0.5%

Most occurring characters

ValueCountFrequency (%)
304705
95.2%
1 7439
 
2.3%
5 4855
 
1.5%
6 1554
 
0.5%
2 822
 
0.3%
3 501
 
0.2%
4 76
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 304705
95.2%
Decimal Number 15247
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7439
48.8%
5 4855
31.8%
6 1554
 
10.2%
2 822
 
5.4%
3 501
 
3.3%
4 76
 
0.5%
Space Separator
ValueCountFrequency (%)
304705
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
304705
95.2%
1 7439
 
2.3%
5 4855
 
1.5%
6 1554
 
0.5%
2 822
 
0.3%
3 501
 
0.2%
4 76
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
304705
95.2%
1 7439
 
2.3%
5 4855
 
1.5%
6 1554
 
0.5%
2 822
 
0.3%
3 501
 
0.2%
4 76
 
< 0.1%

NPCFP24A
Categorical

IMBALANCE 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
312513 
2
 
3298
1
 
3098
3
 
713
4
 
196
Other values (6)
 
134

Length

Max length2
Median length1
Mean length1.0000063
Min length1

Characters and Unicode

Total characters319954
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
312513
97.7%
2 3298
 
1.0%
1 3098
 
1.0%
3 713
 
0.2%
4 196
 
0.1%
5 76
 
< 0.1%
6 35
 
< 0.1%
7 11
 
< 0.1%
8 7
 
< 0.1%
9 3
 
< 0.1%

Length

2024-05-06T23:59:22.747720image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 3298
44.3%
1 3098
41.6%
3 713
 
9.6%
4 196
 
2.6%
5 76
 
1.0%
6 35
 
0.5%
7 11
 
0.1%
8 7
 
0.1%
9 3
 
< 0.1%
11 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
312513
97.7%
2 3298
 
1.0%
1 3102
 
1.0%
3 713
 
0.2%
4 196
 
0.1%
5 76
 
< 0.1%
6 35
 
< 0.1%
7 11
 
< 0.1%
8 7
 
< 0.1%
9 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 312513
97.7%
Decimal Number 7441
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3298
44.3%
1 3102
41.7%
3 713
 
9.6%
4 196
 
2.6%
5 76
 
1.0%
6 35
 
0.5%
7 11
 
0.1%
8 7
 
0.1%
9 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
312513
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319954
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
312513
97.7%
2 3298
 
1.0%
1 3102
 
1.0%
3 713
 
0.2%
4 196
 
0.1%
5 76
 
< 0.1%
6 35
 
< 0.1%
7 11
 
< 0.1%
8 7
 
< 0.1%
9 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319954
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
312513
97.7%
2 3298
 
1.0%
1 3102
 
1.0%
3 713
 
0.2%
4 196
 
0.1%
5 76
 
< 0.1%
6 35
 
< 0.1%
7 11
 
< 0.1%
8 7
 
< 0.1%
9 3
 
< 0.1%

NPCFP24B
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
319130 
2
 
666
1
 
156

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
319130
99.7%
2 666
 
0.2%
1 156
 
< 0.1%

Length

2024-05-06T23:59:22.863155image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:22.961160image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 666
81.0%
1 156
 
19.0%

Most occurring characters

ValueCountFrequency (%)
319130
99.7%
2 666
 
0.2%
1 156
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 319130
99.7%
Decimal Number 822
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 666
81.0%
1 156
 
19.0%
Space Separator
ValueCountFrequency (%)
319130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
319130
99.7%
2 666
 
0.2%
1 156
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319130
99.7%
2 666
 
0.2%
1 156
 
< 0.1%

NPCFP24C
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
319451 
2
 
476
1
 
25

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
319451
99.8%
2 476
 
0.1%
1 25
 
< 0.1%

Length

2024-05-06T23:59:23.064724image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:23.161633image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 476
95.0%
1 25
 
5.0%

Most occurring characters

ValueCountFrequency (%)
319451
99.8%
2 476
 
0.1%
1 25
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 319451
99.8%
Decimal Number 501
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 476
95.0%
1 25
 
5.0%
Space Separator
ValueCountFrequency (%)
319451
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
319451
99.8%
2 476
 
0.1%
1 25
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319451
99.8%
2 476
 
0.1%
1 25
 
< 0.1%

NPCFP25A
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
319833 
1
 
119

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
319833
> 99.9%
1 119
 
< 0.1%

Length

2024-05-06T23:59:23.266221image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:23.360997image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 119
100.0%

Most occurring characters

ValueCountFrequency (%)
319833
> 99.9%
1 119
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 319833
> 99.9%
Decimal Number 119
 
< 0.1%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
319833
100.0%
Decimal Number
ValueCountFrequency (%)
1 119
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
319833
> 99.9%
1 119
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319833
> 99.9%
1 119
 
< 0.1%

NPCFP25B
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
319634 
1
 
318

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
319634
99.9%
1 318
 
0.1%

Length

2024-05-06T23:59:23.461864image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:23.558175image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 318
100.0%

Most occurring characters

ValueCountFrequency (%)
319634
99.9%
1 318
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 319634
99.9%
Decimal Number 318
 
0.1%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
319634
100.0%
Decimal Number
ValueCountFrequency (%)
1 318
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
319634
99.9%
1 318
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319634
99.9%
1 318
 
0.1%

NPCFP25BA
Text

Distinct69
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:23.717519image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0048726
Min length1

Characters and Unicode

Total characters321511
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)< 0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
1000000 55
17.3%
500000 23
 
7.2%
800000 18
 
5.7%
200000 18
 
5.7%
300000 15
 
4.7%
400000 14
 
4.4%
600000 13
 
4.1%
99 13
 
4.1%
100000 10
 
3.1%
700000 10
 
3.1%
Other values (58) 129
40.6%
2024-05-06T23:59:24.072996image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
319634
99.4%
0 1380
 
0.4%
1 100
 
< 0.1%
7 89
 
< 0.1%
5 77
 
< 0.1%
3 51
 
< 0.1%
2 45
 
< 0.1%
8 41
 
< 0.1%
9 37
 
< 0.1%
4 35
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 319634
99.4%
Decimal Number 1877
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1380
73.5%
1 100
 
5.3%
7 89
 
4.7%
5 77
 
4.1%
3 51
 
2.7%
2 45
 
2.4%
8 41
 
2.2%
9 37
 
2.0%
4 35
 
1.9%
6 22
 
1.2%
Space Separator
ValueCountFrequency (%)
319634
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 321511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
319634
99.4%
0 1380
 
0.4%
1 100
 
< 0.1%
7 89
 
< 0.1%
5 77
 
< 0.1%
3 51
 
< 0.1%
2 45
 
< 0.1%
8 41
 
< 0.1%
9 37
 
< 0.1%
4 35
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 321511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319634
99.4%
0 1380
 
0.4%
1 100
 
< 0.1%
7 89
 
< 0.1%
5 77
 
< 0.1%
3 51
 
< 0.1%
2 45
 
< 0.1%
8 41
 
< 0.1%
9 37
 
< 0.1%
4 35
 
< 0.1%

NPCFP25C
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
319788 
1
 
164

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
319788
99.9%
1 164
 
0.1%

Length

2024-05-06T23:59:24.237943image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:24.334335image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 164
100.0%

Most occurring characters

ValueCountFrequency (%)
319788
99.9%
1 164
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 319788
99.9%
Decimal Number 164
 
0.1%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
319788
100.0%
Decimal Number
ValueCountFrequency (%)
1 164
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
319788
99.9%
1 164
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319788
99.9%
1 164
 
0.1%

NPCFP25E
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
319947 
1
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
319947
> 99.9%
1 5
 
< 0.1%

Length

2024-05-06T23:59:24.437945image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:24.533255image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 5
100.0%

Most occurring characters

ValueCountFrequency (%)
319947
> 99.9%
1 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 319947
> 99.9%
Decimal Number 5
 
< 0.1%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
319947
100.0%
Decimal Number
ValueCountFrequency (%)
1 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
319947
> 99.9%
1 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319947
> 99.9%
1 5
 
< 0.1%

NPCFP25F
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
319931 
1
 
21

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
319931
> 99.9%
1 21
 
< 0.1%

Length

2024-05-06T23:59:24.634448image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:24.734655image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 21
100.0%

Most occurring characters

ValueCountFrequency (%)
319931
> 99.9%
1 21
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 319931
> 99.9%
Decimal Number 21
 
< 0.1%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
319931
100.0%
Decimal Number
ValueCountFrequency (%)
1 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
319931
> 99.9%
1 21
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319931
> 99.9%
1 21
 
< 0.1%

NPCFP26
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
302875 
1
 
17077

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 302875
94.7%
1 17077
 
5.3%

Length

2024-05-06T23:59:24.844888image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:24.940767image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 302875
94.7%
1 17077
 
5.3%

Most occurring characters

ValueCountFrequency (%)
2 302875
94.7%
1 17077
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 302875
94.7%
1 17077
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 302875
94.7%
1 17077
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 302875
94.7%
1 17077
 
5.3%

NPCFP26A
Categorical

IMBALANCE 

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
302875 
1
 
12774
2
 
2746
3
 
941
4
 
324
Other values (8)
 
292

Length

Max length2
Median length1
Mean length1.0001531
Min length1

Characters and Unicode

Total characters320001
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row
2nd row1
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
302875
94.7%
1 12774
 
4.0%
2 2746
 
0.9%
3 941
 
0.3%
4 324
 
0.1%
5 125
 
< 0.1%
6 77
 
< 0.1%
10 28
 
< 0.1%
7 21
 
< 0.1%
12 20
 
< 0.1%
Other values (3) 21
 
< 0.1%

Length

2024-05-06T23:59:25.046929image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 12774
74.8%
2 2746
 
16.1%
3 941
 
5.5%
4 324
 
1.9%
5 125
 
0.7%
6 77
 
0.5%
10 28
 
0.2%
7 21
 
0.1%
12 20
 
0.1%
8 19
 
0.1%
Other values (2) 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
302875
94.6%
1 12824
 
4.0%
2 2766
 
0.9%
3 941
 
0.3%
4 324
 
0.1%
5 125
 
< 0.1%
6 77
 
< 0.1%
0 28
 
< 0.1%
7 21
 
< 0.1%
8 19
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 302875
94.6%
Decimal Number 17126
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12824
74.9%
2 2766
 
16.2%
3 941
 
5.5%
4 324
 
1.9%
5 125
 
0.7%
6 77
 
0.4%
0 28
 
0.2%
7 21
 
0.1%
8 19
 
0.1%
9 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
302875
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 320001
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
302875
94.6%
1 12824
 
4.0%
2 2766
 
0.9%
3 941
 
0.3%
4 324
 
0.1%
5 125
 
< 0.1%
6 77
 
< 0.1%
0 28
 
< 0.1%
7 21
 
< 0.1%
8 19
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 320001
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
302875
94.6%
1 12824
 
4.0%
2 2766
 
0.9%
3 941
 
0.3%
4 324
 
0.1%
5 125
 
< 0.1%
6 77
 
< 0.1%
0 28
 
< 0.1%
7 21
 
< 0.1%
8 19
 
< 0.1%

NPCFP27
Text

Distinct494
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:25.298991image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.1258845
Min length1

Characters and Unicode

Total characters360229
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique223 ?
Unique (%)0.1%

Sample

1st row
2nd row0
3rd row
4th row
5th row
ValueCountFrequency (%)
0 8320
48.7%
200000 716
 
4.2%
300000 643
 
3.8%
100000 629
 
3.7%
500000 425
 
2.5%
50000 374
 
2.2%
150000 325
 
1.9%
1000000 285
 
1.7%
400000 285
 
1.7%
2900 275
 
1.6%
Other values (483) 4800
28.1%
2024-05-06T23:59:25.740290image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
302875
84.1%
0 44864
 
12.5%
1 2807
 
0.8%
2 2660
 
0.7%
5 2077
 
0.6%
3 1512
 
0.4%
9 890
 
0.2%
4 766
 
0.2%
8 685
 
0.2%
6 654
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 302875
84.1%
Decimal Number 57354
 
15.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44864
78.2%
1 2807
 
4.9%
2 2660
 
4.6%
5 2077
 
3.6%
3 1512
 
2.6%
9 890
 
1.6%
4 766
 
1.3%
8 685
 
1.2%
6 654
 
1.1%
7 439
 
0.8%
Space Separator
ValueCountFrequency (%)
302875
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 360229
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
302875
84.1%
0 44864
 
12.5%
1 2807
 
0.8%
2 2660
 
0.7%
5 2077
 
0.6%
3 1512
 
0.4%
9 890
 
0.2%
4 766
 
0.2%
8 685
 
0.2%
6 654
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 360229
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
302875
84.1%
0 44864
 
12.5%
1 2807
 
0.8%
2 2660
 
0.7%
5 2077
 
0.6%
3 1512
 
0.4%
9 890
 
0.2%
4 766
 
0.2%
8 685
 
0.2%
6 654
 
0.2%

NPCFP29
Categorical

IMBALANCE 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
302875 
2
 
10965
1
 
3439
3
 
2012
4
 
452

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row1
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
302875
94.7%
2 10965
 
3.4%
1 3439
 
1.1%
3 2012
 
0.6%
4 452
 
0.1%
5 209
 
0.1%

Length

2024-05-06T23:59:25.909080image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:26.017917image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 10965
64.2%
1 3439
 
20.1%
3 2012
 
11.8%
4 452
 
2.6%
5 209
 
1.2%

Most occurring characters

ValueCountFrequency (%)
302875
94.7%
2 10965
 
3.4%
1 3439
 
1.1%
3 2012
 
0.6%
4 452
 
0.1%
5 209
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 302875
94.7%
Decimal Number 17077
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10965
64.2%
1 3439
 
20.1%
3 2012
 
11.8%
4 452
 
2.6%
5 209
 
1.2%
Space Separator
ValueCountFrequency (%)
302875
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
302875
94.7%
2 10965
 
3.4%
1 3439
 
1.1%
3 2012
 
0.6%
4 452
 
0.1%
5 209
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
302875
94.7%
2 10965
 
3.4%
1 3439
 
1.1%
3 2012
 
0.6%
4 452
 
0.1%
5 209
 
0.1%

NPCFP30
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
303337 
1
 
16615

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 303337
94.8%
1 16615
 
5.2%

Length

2024-05-06T23:59:26.132790image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:26.231431image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 303337
94.8%
1 16615
 
5.2%

Most occurring characters

ValueCountFrequency (%)
2 303337
94.8%
1 16615
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 303337
94.8%
1 16615
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 303337
94.8%
1 16615
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 303337
94.8%
1 16615
 
5.2%

NPCFP31
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
303337 
1
 
15477
2
 
1138

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
303337
94.8%
1 15477
 
4.8%
2 1138
 
0.4%

Length

2024-05-06T23:59:26.332576image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:26.432452image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 15477
93.2%
2 1138
 
6.8%

Most occurring characters

ValueCountFrequency (%)
303337
94.8%
1 15477
 
4.8%
2 1138
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 303337
94.8%
Decimal Number 16615
 
5.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15477
93.2%
2 1138
 
6.8%
Space Separator
ValueCountFrequency (%)
303337
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
303337
94.8%
1 15477
 
4.8%
2 1138
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
303337
94.8%
1 15477
 
4.8%
2 1138
 
0.4%

NPCFP32
Categorical

IMBALANCE 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
304475 
1
 
4358
2
 
3204
5
 
3034
4
 
2601

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
304475
95.2%
1 4358
 
1.4%
2 3204
 
1.0%
5 3034
 
0.9%
4 2601
 
0.8%
3 2280
 
0.7%

Length

2024-05-06T23:59:26.540349image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:26.647566image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 4358
28.2%
2 3204
20.7%
5 3034
19.6%
4 2601
16.8%
3 2280
14.7%

Most occurring characters

ValueCountFrequency (%)
304475
95.2%
1 4358
 
1.4%
2 3204
 
1.0%
5 3034
 
0.9%
4 2601
 
0.8%
3 2280
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Space Separator 304475
95.2%
Decimal Number 15477
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4358
28.2%
2 3204
20.7%
5 3034
19.6%
4 2601
16.8%
3 2280
14.7%
Space Separator
ValueCountFrequency (%)
304475
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
304475
95.2%
1 4358
 
1.4%
2 3204
 
1.0%
5 3034
 
0.9%
4 2601
 
0.8%
3 2280
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
304475
95.2%
1 4358
 
1.4%
2 3204
 
1.0%
5 3034
 
0.9%
4 2601
 
0.8%
3 2280
 
0.7%

NPCFP33A
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
252731 
1
67221 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 252731
79.0%
1 67221
 
21.0%

Length

2024-05-06T23:59:26.765646image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:26.861539image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 252731
79.0%
1 67221
 
21.0%

Most occurring characters

ValueCountFrequency (%)
2 252731
79.0%
1 67221
 
21.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 252731
79.0%
1 67221
 
21.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 252731
79.0%
1 67221
 
21.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 252731
79.0%
1 67221
 
21.0%

NPCFP33AA
Text

Distinct451
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:27.103367image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.4928208
Min length1

Characters and Unicode

Total characters477631
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)< 0.1%

Sample

1st row
2nd row19000
3rd row2500
4th row
5th row0
ValueCountFrequency (%)
0 20465
30.4%
2900 19685
29.3%
10000 2688
 
4.0%
3000 2306
 
3.4%
30000 1706
 
2.5%
20000 1618
 
2.4%
11300 1164
 
1.7%
5000 1059
 
1.6%
15000 948
 
1.4%
2700 892
 
1.3%
Other values (440) 14690
21.9%
2024-05-06T23:59:27.525732image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
252731
52.9%
0 142163
29.8%
2 28468
 
6.0%
9 22238
 
4.7%
1 12279
 
2.6%
3 7118
 
1.5%
5 5212
 
1.1%
8 1975
 
0.4%
7 1905
 
0.4%
4 1775
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 252731
52.9%
Decimal Number 224900
47.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 142163
63.2%
2 28468
 
12.7%
9 22238
 
9.9%
1 12279
 
5.5%
3 7118
 
3.2%
5 5212
 
2.3%
8 1975
 
0.9%
7 1905
 
0.8%
4 1775
 
0.8%
6 1767
 
0.8%
Space Separator
ValueCountFrequency (%)
252731
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 477631
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
252731
52.9%
0 142163
29.8%
2 28468
 
6.0%
9 22238
 
4.7%
1 12279
 
2.6%
3 7118
 
1.5%
5 5212
 
1.1%
8 1975
 
0.4%
7 1905
 
0.4%
4 1775
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 477631
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
252731
52.9%
0 142163
29.8%
2 28468
 
6.0%
9 22238
 
4.7%
1 12279
 
2.6%
3 7118
 
1.5%
5 5212
 
1.1%
8 1975
 
0.4%
7 1905
 
0.4%
4 1775
 
0.4%

NPCFP33B
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
287744 
1
32208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 287744
89.9%
1 32208
 
10.1%

Length

2024-05-06T23:59:27.707141image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:27.802368image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 287744
89.9%
1 32208
 
10.1%

Most occurring characters

ValueCountFrequency (%)
2 287744
89.9%
1 32208
 
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 287744
89.9%
1 32208
 
10.1%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 287744
89.9%
1 32208
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 287744
89.9%
1 32208
 
10.1%

NPCFP33BA
Text

Distinct449
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:28.050667image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.2536756
Min length1

Characters and Unicode

Total characters401116
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)< 0.1%

Sample

1st row
2nd row19000
3rd row
4th row
5th row
ValueCountFrequency (%)
0 9412
29.2%
2900 7529
23.4%
30000 1358
 
4.2%
10000 1045
 
3.2%
20000 955
 
3.0%
3000 820
 
2.5%
11300 620
 
1.9%
50000 539
 
1.7%
15000 434
 
1.3%
25000 396
 
1.2%
Other values (438) 9100
28.3%
2024-05-06T23:59:28.499260image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
287744
71.7%
0 73059
 
18.2%
2 12879
 
3.2%
9 9378
 
2.3%
1 6784
 
1.7%
3 4029
 
1.0%
5 2887
 
0.7%
7 1167
 
0.3%
8 1146
 
0.3%
4 1027
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 287744
71.7%
Decimal Number 113372
 
28.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 73059
64.4%
2 12879
 
11.4%
9 9378
 
8.3%
1 6784
 
6.0%
3 4029
 
3.6%
5 2887
 
2.5%
7 1167
 
1.0%
8 1146
 
1.0%
4 1027
 
0.9%
6 1016
 
0.9%
Space Separator
ValueCountFrequency (%)
287744
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 401116
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
287744
71.7%
0 73059
 
18.2%
2 12879
 
3.2%
9 9378
 
2.3%
1 6784
 
1.7%
3 4029
 
1.0%
5 2887
 
0.7%
7 1167
 
0.3%
8 1146
 
0.3%
4 1027
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 401116
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
287744
71.7%
0 73059
 
18.2%
2 12879
 
3.2%
9 9378
 
2.3%
1 6784
 
1.7%
3 4029
 
1.0%
5 2887
 
0.7%
7 1167
 
0.3%
8 1146
 
0.3%
4 1027
 
0.3%

NPCFP33C
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
294952 
1
 
25000

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 294952
92.2%
1 25000
 
7.8%

Length

2024-05-06T23:59:28.673151image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:28.769482image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 294952
92.2%
1 25000
 
7.8%

Most occurring characters

ValueCountFrequency (%)
2 294952
92.2%
1 25000
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 294952
92.2%
1 25000
 
7.8%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 294952
92.2%
1 25000
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 294952
92.2%
1 25000
 
7.8%

NPCFP33CA
Text

Distinct442
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:29.011545image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.2140665
Min length1

Characters and Unicode

Total characters388443
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique172 ?
Unique (%)0.1%

Sample

1st row
2nd row
3rd row
4th row10000
5th row
ValueCountFrequency (%)
0 6595
26.4%
2900 5393
21.6%
50000 913
 
3.7%
10000 673
 
2.7%
3000 587
 
2.3%
30000 583
 
2.3%
20000 495
 
2.0%
100000 443
 
1.8%
60000 429
 
1.7%
5000 303
 
1.2%
Other values (431) 8586
34.3%
2024-05-06T23:59:29.447445image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
294952
75.9%
0 63158
 
16.3%
2 8946
 
2.3%
9 6330
 
1.6%
1 4527
 
1.2%
5 3537
 
0.9%
3 2651
 
0.7%
6 1136
 
0.3%
8 1123
 
0.3%
4 1080
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 294952
75.9%
Decimal Number 93491
 
24.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 63158
67.6%
2 8946
 
9.6%
9 6330
 
6.8%
1 4527
 
4.8%
5 3537
 
3.8%
3 2651
 
2.8%
6 1136
 
1.2%
8 1123
 
1.2%
4 1080
 
1.2%
7 1003
 
1.1%
Space Separator
ValueCountFrequency (%)
294952
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 388443
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
294952
75.9%
0 63158
 
16.3%
2 8946
 
2.3%
9 6330
 
1.6%
1 4527
 
1.2%
5 3537
 
0.9%
3 2651
 
0.7%
6 1136
 
0.3%
8 1123
 
0.3%
4 1080
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 388443
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
294952
75.9%
0 63158
 
16.3%
2 8946
 
2.3%
9 6330
 
1.6%
1 4527
 
1.2%
5 3537
 
0.9%
3 2651
 
0.7%
6 1136
 
0.3%
8 1123
 
0.3%
4 1080
 
0.3%

NPCFP33D
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
309794 
1
 
10158

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 309794
96.8%
1 10158
 
3.2%

Length

2024-05-06T23:59:29.620678image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:29.719393image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 309794
96.8%
1 10158
 
3.2%

Most occurring characters

ValueCountFrequency (%)
2 309794
96.8%
1 10158
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 309794
96.8%
1 10158
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 309794
96.8%
1 10158
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 309794
96.8%
1 10158
 
3.2%

NPCFP33DA
Text

Distinct196
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:29.868963image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0237879
Min length1

Characters and Unicode

Total characters327563
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)< 0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
0 8075
79.5%
2900 509
 
5.0%
10000 179
 
1.8%
20000 106
 
1.0%
5000 75
 
0.7%
30000 71
 
0.7%
3000 61
 
0.6%
99 50
 
0.5%
50000 48
 
0.5%
15000 44
 
0.4%
Other values (185) 940
 
9.3%
2024-05-06T23:59:30.204607image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
309794
94.6%
0 14409
 
4.4%
2 974
 
0.3%
9 690
 
0.2%
1 542
 
0.2%
5 363
 
0.1%
3 291
 
0.1%
8 150
 
< 0.1%
4 142
 
< 0.1%
6 122
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 309794
94.6%
Decimal Number 17769
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14409
81.1%
2 974
 
5.5%
9 690
 
3.9%
1 542
 
3.1%
5 363
 
2.0%
3 291
 
1.6%
8 150
 
0.8%
4 142
 
0.8%
6 122
 
0.7%
7 86
 
0.5%
Space Separator
ValueCountFrequency (%)
309794
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 327563
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
309794
94.6%
0 14409
 
4.4%
2 974
 
0.3%
9 690
 
0.2%
1 542
 
0.2%
5 363
 
0.1%
3 291
 
0.1%
8 150
 
< 0.1%
4 142
 
< 0.1%
6 122
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 327563
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
309794
94.6%
0 14409
 
4.4%
2 974
 
0.3%
9 690
 
0.2%
1 542
 
0.2%
5 363
 
0.1%
3 291
 
0.1%
8 150
 
< 0.1%
4 142
 
< 0.1%
6 122
 
< 0.1%

NPCFP33E
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
299542 
1
 
20410

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 299542
93.6%
1 20410
 
6.4%

Length

2024-05-06T23:59:30.660075image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:30.756341image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 299542
93.6%
1 20410
 
6.4%

Most occurring characters

ValueCountFrequency (%)
2 299542
93.6%
1 20410
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 299542
93.6%
1 20410
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 299542
93.6%
1 20410
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 299542
93.6%
1 20410
 
6.4%

NPCFP33EA
Text

Distinct404
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:30.969034image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.1402742
Min length1

Characters and Unicode

Total characters364833
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)< 0.1%

Sample

1st row
2nd row19000
3rd row
4th row
5th row
ValueCountFrequency (%)
0 7683
37.6%
2900 4340
21.3%
30000 672
 
3.3%
10000 539
 
2.6%
3000 502
 
2.5%
20000 454
 
2.2%
11300 377
 
1.8%
50000 317
 
1.6%
15000 270
 
1.3%
12000 240
 
1.2%
Other values (393) 5016
24.6%
2024-05-06T23:59:31.371501image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
299542
82.1%
0 42810
 
11.7%
2 6938
 
1.9%
9 5443
 
1.5%
1 3778
 
1.0%
3 2205
 
0.6%
5 1707
 
0.5%
8 649
 
0.2%
6 613
 
0.2%
4 581
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 299542
82.1%
Decimal Number 65291
 
17.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 42810
65.6%
2 6938
 
10.6%
9 5443
 
8.3%
1 3778
 
5.8%
3 2205
 
3.4%
5 1707
 
2.6%
8 649
 
1.0%
6 613
 
0.9%
4 581
 
0.9%
7 567
 
0.9%
Space Separator
ValueCountFrequency (%)
299542
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 364833
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
299542
82.1%
0 42810
 
11.7%
2 6938
 
1.9%
9 5443
 
1.5%
1 3778
 
1.0%
3 2205
 
0.6%
5 1707
 
0.5%
8 649
 
0.2%
6 613
 
0.2%
4 581
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 364833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
299542
82.1%
0 42810
 
11.7%
2 6938
 
1.9%
9 5443
 
1.5%
1 3778
 
1.0%
3 2205
 
0.6%
5 1707
 
0.5%
8 649
 
0.2%
6 613
 
0.2%
4 581
 
0.2%

NPCFP33F
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
316624 
1
 
3328

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 316624
99.0%
1 3328
 
1.0%

Length

2024-05-06T23:59:31.538451image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:31.638442image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 316624
99.0%
1 3328
 
1.0%

Most occurring characters

ValueCountFrequency (%)
2 316624
99.0%
1 3328
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 316624
99.0%
1 3328
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 316624
99.0%
1 3328
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 316624
99.0%
1 3328
 
1.0%

NPCFP33FA
Text

Distinct213
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:31.805662image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0295951
Min length1

Characters and Unicode

Total characters329421
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)< 0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
0 1052
31.6%
2900 229
 
6.9%
100000 156
 
4.7%
50000 135
 
4.1%
200000 101
 
3.0%
30000 96
 
2.9%
150000 92
 
2.8%
20000 86
 
2.6%
10000 76
 
2.3%
60000 71
 
2.1%
Other values (202) 1234
37.1%
2024-05-06T23:59:32.151814image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
316624
96.1%
0 9403
 
2.9%
2 769
 
0.2%
1 715
 
0.2%
5 548
 
0.2%
9 370
 
0.1%
3 317
 
0.1%
4 189
 
0.1%
6 186
 
0.1%
8 164
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 316624
96.1%
Decimal Number 12797
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9403
73.5%
2 769
 
6.0%
1 715
 
5.6%
5 548
 
4.3%
9 370
 
2.9%
3 317
 
2.5%
4 189
 
1.5%
6 186
 
1.5%
8 164
 
1.3%
7 136
 
1.1%
Space Separator
ValueCountFrequency (%)
316624
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 329421
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
316624
96.1%
0 9403
 
2.9%
2 769
 
0.2%
1 715
 
0.2%
5 548
 
0.2%
9 370
 
0.1%
3 317
 
0.1%
4 189
 
0.1%
6 186
 
0.1%
8 164
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 329421
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
316624
96.1%
0 9403
 
2.9%
2 769
 
0.2%
1 715
 
0.2%
5 548
 
0.2%
9 370
 
0.1%
3 317
 
0.1%
4 189
 
0.1%
6 186
 
0.1%
8 164
 
< 0.1%

NPCFP34
Real number (ℝ)

SKEWED  ZEROS 

Distinct675
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14543.331
Minimum0
Maximum5000000
Zeros243848
Zeros (%)76.2%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:32.327871image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile70000
Maximum5000000
Range5000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation81511.463
Coefficient of variation (CV)5.6047316
Kurtosis1030.7387
Mean14543.331
Median Absolute Deviation (MAD)0
Skewness24.430568
Sum4.6531677 × 109
Variance6.6441187 × 109
MonotonicityNot monotonic
2024-05-06T23:59:32.483748image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 243848
76.2%
2900 7508
 
2.3%
20000 6826
 
2.1%
10000 6813
 
2.1%
30000 5228
 
1.6%
50000 5091
 
1.6%
5000 3522
 
1.1%
100000 3374
 
1.1%
15000 2863
 
0.9%
40000 2163
 
0.7%
Other values (665) 32716
 
10.2%
ValueCountFrequency (%)
0 243848
76.2%
98 46
 
< 0.1%
99 588
 
0.2%
100 4
 
< 0.1%
120 5
 
< 0.1%
150 1
 
< 0.1%
200 1
 
< 0.1%
290 1
 
< 0.1%
300 4
 
< 0.1%
400 1
 
< 0.1%
ValueCountFrequency (%)
5000000 13
< 0.1%
4500000 1
 
< 0.1%
4000000 5
 
< 0.1%
3840000 1
 
< 0.1%
3800000 1
 
< 0.1%
3600000 1
 
< 0.1%
3590000 1
 
< 0.1%
3500000 2
 
< 0.1%
3400000 1
 
< 0.1%
3000000 21
< 0.1%

NPCFP35A
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
292625 
1
 
27327

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
2 292625
91.5%
1 27327
 
8.5%

Length

2024-05-06T23:59:32.623572image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:32.724199image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 292625
91.5%
1 27327
 
8.5%

Most occurring characters

ValueCountFrequency (%)
2 292625
91.5%
1 27327
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 292625
91.5%
1 27327
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 292625
91.5%
1 27327
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 292625
91.5%
1 27327
 
8.5%

NPCFP35AA
Text

Distinct539
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:33.009325image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.418219
Min length1

Characters and Unicode

Total characters453762
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique223 ?
Unique (%)0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row150000
ValueCountFrequency (%)
300000 2267
 
8.3%
200000 2097
 
7.7%
150000 1658
 
6.1%
400000 1553
 
5.7%
250000 1519
 
5.6%
500000 1192
 
4.4%
350000 1098
 
4.0%
120000 1034
 
3.8%
100000 950
 
3.5%
180000 907
 
3.3%
Other values (528) 13052
47.8%
2024-05-06T23:59:33.480615image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
292625
64.5%
0 118512
26.1%
5 8229
 
1.8%
2 8051
 
1.8%
1 8027
 
1.8%
3 5774
 
1.3%
4 3742
 
0.8%
8 3373
 
0.7%
6 2392
 
0.5%
7 1751
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 292625
64.5%
Decimal Number 161137
35.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 118512
73.5%
5 8229
 
5.1%
2 8051
 
5.0%
1 8027
 
5.0%
3 5774
 
3.6%
4 3742
 
2.3%
8 3373
 
2.1%
6 2392
 
1.5%
7 1751
 
1.1%
9 1286
 
0.8%
Space Separator
ValueCountFrequency (%)
292625
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 453762
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
292625
64.5%
0 118512
26.1%
5 8229
 
1.8%
2 8051
 
1.8%
1 8027
 
1.8%
3 5774
 
1.3%
4 3742
 
0.8%
8 3373
 
0.7%
6 2392
 
0.5%
7 1751
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 453762
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
292625
64.5%
0 118512
26.1%
5 8229
 
1.8%
2 8051
 
1.8%
1 8027
 
1.8%
3 5774
 
1.3%
4 3742
 
0.8%
8 3373
 
0.7%
6 2392
 
0.5%
7 1751
 
0.4%

NPCFP35B
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
310869 
1
 
9083

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
2 310869
97.2%
1 9083
 
2.8%

Length

2024-05-06T23:59:33.644745image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:33.743164image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 310869
97.2%
1 9083
 
2.8%

Most occurring characters

ValueCountFrequency (%)
2 310869
97.2%
1 9083
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 319952
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 310869
97.2%
1 9083
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 310869
97.2%
1 9083
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 310869
97.2%
1 9083
 
2.8%

NPCFP35BA
Text

Distinct499
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2024-05-06T23:59:34.012775image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length8
Median length1
Mean length1.1174426
Min length1

Characters and Unicode

Total characters357528
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique235 ?
Unique (%)0.1%

Sample

1st row
2nd row
3rd row
4th row40000
5th row
ValueCountFrequency (%)
2900 881
 
9.7%
1000 577
 
6.4%
200000 416
 
4.6%
100000 415
 
4.6%
99 388
 
4.3%
50000 356
 
3.9%
300000 311
 
3.4%
30000 262
 
2.9%
10000 232
 
2.6%
500000 230
 
2.5%
Other values (488) 5015
55.2%
2024-05-06T23:59:34.456730image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310869
86.9%
0 32968
 
9.2%
1 3010
 
0.8%
2 2867
 
0.8%
9 2180
 
0.6%
5 1793
 
0.5%
3 1355
 
0.4%
8 811
 
0.2%
6 649
 
0.2%
4 645
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 310869
86.9%
Decimal Number 46659
 
13.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 32968
70.7%
1 3010
 
6.5%
2 2867
 
6.1%
9 2180
 
4.7%
5 1793
 
3.8%
3 1355
 
2.9%
8 811
 
1.7%
6 649
 
1.4%
4 645
 
1.4%
7 381
 
0.8%
Space Separator
ValueCountFrequency (%)
310869
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 357528
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
310869
86.9%
0 32968
 
9.2%
1 3010
 
0.8%
2 2867
 
0.8%
9 2180
 
0.6%
5 1793
 
0.5%
3 1355
 
0.4%
8 811
 
0.2%
6 649
 
0.2%
4 645
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 357528
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
310869
86.9%
0 32968
 
9.2%
1 3010
 
0.8%
2 2867
 
0.8%
9 2180
 
0.6%
5 1793
 
0.5%
3 1355
 
0.4%
8 811
 
0.2%
6 649
 
0.2%
4 645
 
0.2%

NPCFP36
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
4
142195 
2
60231 
1
51373 
38770 
3
27383 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row4
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
4 142195
44.4%
2 60231
18.8%
1 51373
 
16.1%
38770
 
12.1%
3 27383
 
8.6%

Length

2024-05-06T23:59:34.623318image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:34.733011image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
4 142195
50.6%
2 60231
21.4%
1 51373
 
18.3%
3 27383
 
9.7%

Most occurring characters

ValueCountFrequency (%)
4 142195
44.4%
2 60231
18.8%
1 51373
 
16.1%
38770
 
12.1%
3 27383
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 281182
87.9%
Space Separator 38770
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 142195
50.6%
2 60231
21.4%
1 51373
 
18.3%
3 27383
 
9.7%
Space Separator
ValueCountFrequency (%)
38770
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 142195
44.4%
2 60231
18.8%
1 51373
 
16.1%
38770
 
12.1%
3 27383
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 142195
44.4%
2 60231
18.8%
1 51373
 
16.1%
38770
 
12.1%
3 27383
 
8.6%

NPCFP37
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
177757 
3
71019 
2
37715 
1
25855 
6
 
3300
Other values (2)
 
4306

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row3
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
177757
55.6%
3 71019
 
22.2%
2 37715
 
11.8%
1 25855
 
8.1%
6 3300
 
1.0%
4 2821
 
0.9%
5 1485
 
0.5%

Length

2024-05-06T23:59:34.851990image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:34.962842image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
3 71019
49.9%
2 37715
26.5%
1 25855
 
18.2%
6 3300
 
2.3%
4 2821
 
2.0%
5 1485
 
1.0%

Most occurring characters

ValueCountFrequency (%)
177757
55.6%
3 71019
 
22.2%
2 37715
 
11.8%
1 25855
 
8.1%
6 3300
 
1.0%
4 2821
 
0.9%
5 1485
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 177757
55.6%
Decimal Number 142195
44.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 71019
49.9%
2 37715
26.5%
1 25855
 
18.2%
6 3300
 
2.3%
4 2821
 
2.0%
5 1485
 
1.0%
Space Separator
ValueCountFrequency (%)
177757
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
177757
55.6%
3 71019
 
22.2%
2 37715
 
11.8%
1 25855
 
8.1%
6 3300
 
1.0%
4 2821
 
0.9%
5 1485
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
177757
55.6%
3 71019
 
22.2%
2 37715
 
11.8%
1 25855
 
8.1%
6 3300
 
1.0%
4 2821
 
0.9%
5 1485
 
0.5%

NPCFP38
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
259606 
38770 
1
 
21576

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 259606
81.1%
38770
 
12.1%
1 21576
 
6.7%

Length

2024-05-06T23:59:35.110347image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:35.206690image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 259606
92.3%
1 21576
 
7.7%

Most occurring characters

ValueCountFrequency (%)
2 259606
81.1%
38770
 
12.1%
1 21576
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 281182
87.9%
Space Separator 38770
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 259606
92.3%
1 21576
 
7.7%
Space Separator
ValueCountFrequency (%)
38770
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 259606
81.1%
38770
 
12.1%
1 21576
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 259606
81.1%
38770
 
12.1%
1 21576
 
6.7%

NPCFP39
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
298376 
1
 
12992
2
 
8584

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
298376
93.3%
1 12992
 
4.1%
2 8584
 
2.7%

Length

2024-05-06T23:59:35.311682image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:35.406816image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 12992
60.2%
2 8584
39.8%

Most occurring characters

ValueCountFrequency (%)
298376
93.3%
1 12992
 
4.1%
2 8584
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Space Separator 298376
93.3%
Decimal Number 21576
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12992
60.2%
2 8584
39.8%
Space Separator
ValueCountFrequency (%)
298376
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
298376
93.3%
1 12992
 
4.1%
2 8584
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
298376
93.3%
1 12992
 
4.1%
2 8584
 
2.7%

NPCFP39A
Categorical

IMBALANCE 

Distinct37
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
306960 
3
 
2227
2
 
2160
5
 
1847
10
 
1811
Other values (32)
 
4947

Length

Max length2
Median length1
Mean length1.0085669
Min length1

Characters and Unicode

Total characters322693
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)< 0.1%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
306960
95.9%
3 2227
 
0.7%
2 2160
 
0.7%
5 1847
 
0.6%
10 1811
 
0.6%
4 1586
 
0.5%
1 1074
 
0.3%
6 722
 
0.2%
20 461
 
0.1%
7 300
 
0.1%
Other values (27) 804
 
0.3%

Length

2024-05-06T23:59:35.517279image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3 2227
17.1%
2 2160
16.6%
5 1847
14.2%
10 1811
13.9%
4 1586
12.2%
1 1074
8.3%
6 722
 
5.6%
20 461
 
3.5%
8 300
 
2.3%
7 300
 
2.3%
Other values (26) 504
 
3.9%

Most occurring characters

ValueCountFrequency (%)
306960
95.1%
1 3243
 
1.0%
2 2772
 
0.9%
0 2364
 
0.7%
3 2301
 
0.7%
5 2043
 
0.6%
4 1630
 
0.5%
6 730
 
0.2%
8 308
 
0.1%
7 304
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 306960
95.1%
Decimal Number 15733
 
4.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3243
20.6%
2 2772
17.6%
0 2364
15.0%
3 2301
14.6%
5 2043
13.0%
4 1630
10.4%
6 730
 
4.6%
8 308
 
2.0%
7 304
 
1.9%
9 38
 
0.2%
Space Separator
ValueCountFrequency (%)
306960
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 322693
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
306960
95.1%
1 3243
 
1.0%
2 2772
 
0.9%
0 2364
 
0.7%
3 2301
 
0.7%
5 2043
 
0.6%
4 1630
 
0.5%
6 730
 
0.2%
8 308
 
0.1%
7 304
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 322693
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
306960
95.1%
1 3243
 
1.0%
2 2772
 
0.9%
0 2364
 
0.7%
3 2301
 
0.7%
5 2043
 
0.6%
4 1630
 
0.5%
6 730
 
0.2%
8 308
 
0.1%
7 304
 
0.1%

NPCFP40A
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
180137 
1
75178 
2
64637 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row2
3rd row2
4th row
5th row1

Common Values

ValueCountFrequency (%)
180137
56.3%
1 75178
23.5%
2 64637
 
20.2%

Length

2024-05-06T23:59:35.631861image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:35.729095image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 75178
53.8%
2 64637
46.2%

Most occurring characters

ValueCountFrequency (%)
180137
56.3%
1 75178
23.5%
2 64637
 
20.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 180137
56.3%
Decimal Number 139815
43.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 75178
53.8%
2 64637
46.2%
Space Separator
ValueCountFrequency (%)
180137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
180137
56.3%
1 75178
23.5%
2 64637
 
20.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180137
56.3%
1 75178
23.5%
2 64637
 
20.2%

NPCFP40B
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
245960 
2
41322 
1
32670 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row2
3rd row
4th row
5th row2

Common Values

ValueCountFrequency (%)
245960
76.9%
2 41322
 
12.9%
1 32670
 
10.2%

Length

2024-05-06T23:59:35.837727image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:35.938190image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 41322
55.8%
1 32670
44.2%

Most occurring characters

ValueCountFrequency (%)
245960
76.9%
2 41322
 
12.9%
1 32670
 
10.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 245960
76.9%
Decimal Number 73992
 
23.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 41322
55.8%
1 32670
44.2%
Space Separator
ValueCountFrequency (%)
245960
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
245960
76.9%
2 41322
 
12.9%
1 32670
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
245960
76.9%
2 41322
 
12.9%
1 32670
 
10.2%

NPCFP40C
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
262191 
2
34906 
1
 
22855

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row
3rd row
4th row2
5th row

Common Values

ValueCountFrequency (%)
262191
81.9%
2 34906
 
10.9%
1 22855
 
7.1%

Length

2024-05-06T23:59:36.047997image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:36.149021image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 34906
60.4%
1 22855
39.6%

Most occurring characters

ValueCountFrequency (%)
262191
81.9%
2 34906
 
10.9%
1 22855
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 262191
81.9%
Decimal Number 57761
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 34906
60.4%
1 22855
39.6%
Space Separator
ValueCountFrequency (%)
262191
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
262191
81.9%
2 34906
 
10.9%
1 22855
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
262191
81.9%
2 34906
 
10.9%
1 22855
 
7.1%

NPCFP40D
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
1
138361 
2
120935 
60656 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 138361
43.2%
2 120935
37.8%
60656
19.0%

Length

2024-05-06T23:59:36.258975image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:36.360057image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 138361
53.4%
2 120935
46.6%

Most occurring characters

ValueCountFrequency (%)
1 138361
43.2%
2 120935
37.8%
60656
19.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 259296
81.0%
Space Separator 60656
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 138361
53.4%
2 120935
46.6%
Space Separator
ValueCountFrequency (%)
60656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 138361
43.2%
2 120935
37.8%
60656
19.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 138361
43.2%
2 120935
37.8%
60656
19.0%

NPCFP40E
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
228058 
60656 
1
31238 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 228058
71.3%
60656
 
19.0%
1 31238
 
9.8%

Length

2024-05-06T23:59:36.476936image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:36.580345image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 228058
88.0%
1 31238
 
12.0%

Most occurring characters

ValueCountFrequency (%)
2 228058
71.3%
60656
 
19.0%
1 31238
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 259296
81.0%
Space Separator 60656
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 228058
88.0%
1 31238
 
12.0%
Space Separator
ValueCountFrequency (%)
60656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 228058
71.3%
60656
 
19.0%
1 31238
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 228058
71.3%
60656
 
19.0%
1 31238
 
9.8%

NPCFP40F
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
2
143457 
1
115839 
60656 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 143457
44.8%
1 115839
36.2%
60656
19.0%

Length

2024-05-06T23:59:36.692466image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:36.792992image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 143457
55.3%
1 115839
44.7%

Most occurring characters

ValueCountFrequency (%)
2 143457
44.8%
1 115839
36.2%
60656
19.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 259296
81.0%
Space Separator 60656
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 143457
55.3%
1 115839
44.7%
Space Separator
ValueCountFrequency (%)
60656
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 143457
44.8%
1 115839
36.2%
60656
19.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 143457
44.8%
1 115839
36.2%
60656
19.0%

NPCFP40
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
220645 
2
54579 
1
44728 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row1
3rd row2
4th row
5th row1

Common Values

ValueCountFrequency (%)
220645
69.0%
2 54579
 
17.1%
1 44728
 
14.0%

Length

2024-05-06T23:59:36.912481image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:37.015849image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
2 54579
55.0%
1 44728
45.0%

Most occurring characters

ValueCountFrequency (%)
220645
69.0%
2 54579
 
17.1%
1 44728
 
14.0%

Most occurring categories

ValueCountFrequency (%)
Space Separator 220645
69.0%
Decimal Number 99307
31.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 54579
55.0%
1 44728
45.0%
Space Separator
ValueCountFrequency (%)
220645
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
220645
69.0%
2 54579
 
17.1%
1 44728
 
14.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
220645
69.0%
2 54579
 
17.1%
1 44728
 
14.0%

NPCFP41
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
275224 
3
41530 
1
 
1864
2
 
1334

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row3
3rd row
4th row
5th row3

Common Values

ValueCountFrequency (%)
275224
86.0%
3 41530
 
13.0%
1 1864
 
0.6%
2 1334
 
0.4%

Length

2024-05-06T23:59:37.128319image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:37.230846image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
3 41530
92.9%
1 1864
 
4.2%
2 1334
 
3.0%

Most occurring characters

ValueCountFrequency (%)
275224
86.0%
3 41530
 
13.0%
1 1864
 
0.6%
2 1334
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator 275224
86.0%
Decimal Number 44728
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 41530
92.9%
1 1864
 
4.2%
2 1334
 
3.0%
Space Separator
ValueCountFrequency (%)
275224
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
275224
86.0%
3 41530
 
13.0%
1 1864
 
0.6%
2 1334
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
275224
86.0%
3 41530
 
13.0%
1 1864
 
0.6%
2 1334
 
0.4%

NPCFP42
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
316754 
1
 
2313
2
 
885

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
316754
99.0%
1 2313
 
0.7%
2 885
 
0.3%

Length

2024-05-06T23:59:37.340709image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:37.437629image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 2313
72.3%
2 885
 
27.7%

Most occurring characters

ValueCountFrequency (%)
316754
99.0%
1 2313
 
0.7%
2 885
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 316754
99.0%
Decimal Number 3198
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2313
72.3%
2 885
 
27.7%
Space Separator
ValueCountFrequency (%)
316754
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
316754
99.0%
1 2313
 
0.7%
2 885
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
316754
99.0%
1 2313
 
0.7%
2 885
 
0.3%

NPCFP43
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
275224 
1
43841 
2
 
887

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row1
3rd row
4th row
5th row1

Common Values

ValueCountFrequency (%)
275224
86.0%
1 43841
 
13.7%
2 887
 
0.3%

Length

2024-05-06T23:59:37.545580image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:37.645739image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 43841
98.0%
2 887
 
2.0%

Most occurring characters

ValueCountFrequency (%)
275224
86.0%
1 43841
 
13.7%
2 887
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 275224
86.0%
Decimal Number 44728
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 43841
98.0%
2 887
 
2.0%
Space Separator
ValueCountFrequency (%)
275224
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
275224
86.0%
1 43841
 
13.7%
2 887
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
275224
86.0%
1 43841
 
13.7%
2 887
 
0.3%

NPCFP43A
Categorical

IMBALANCE 

Distinct40
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
276111 
20
 
4355
19
 
3984
18
 
3884
21
 
3328
Other values (35)
28290 

Length

Max length2
Median length1
Mean length1.1370237
Min length1

Characters and Unicode

Total characters363793
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row
2nd row22
3rd row
4th row
5th row23

Common Values

ValueCountFrequency (%)
276111
86.3%
20 4355
 
1.4%
19 3984
 
1.2%
18 3884
 
1.2%
21 3328
 
1.0%
22 3204
 
1.0%
17 3128
 
1.0%
23 2703
 
0.8%
16 2421
 
0.8%
24 2245
 
0.7%
Other values (30) 14589
 
4.6%

Length

2024-05-06T23:59:37.759382image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20 4355
 
9.9%
19 3984
 
9.1%
18 3884
 
8.9%
21 3328
 
7.6%
22 3204
 
7.3%
17 3128
 
7.1%
23 2703
 
6.2%
16 2421
 
5.5%
24 2245
 
5.1%
25 2191
 
5.0%
Other values (29) 12398
28.3%

Most occurring characters

ValueCountFrequency (%)
276111
75.9%
2 27608
 
7.6%
1 19397
 
5.3%
3 8091
 
2.2%
0 5596
 
1.5%
8 5325
 
1.5%
9 5153
 
1.4%
7 4870
 
1.3%
6 4439
 
1.2%
5 3986
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 276111
75.9%
Decimal Number 87682
 
24.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 27608
31.5%
1 19397
22.1%
3 8091
 
9.2%
0 5596
 
6.4%
8 5325
 
6.1%
9 5153
 
5.9%
7 4870
 
5.6%
6 4439
 
5.1%
5 3986
 
4.5%
4 3217
 
3.7%
Space Separator
ValueCountFrequency (%)
276111
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 363793
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
276111
75.9%
2 27608
 
7.6%
1 19397
 
5.3%
3 8091
 
2.2%
0 5596
 
1.5%
8 5325
 
1.5%
9 5153
 
1.4%
7 4870
 
1.3%
6 4439
 
1.2%
5 3986
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 363793
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
276111
75.9%
2 27608
 
7.6%
1 19397
 
5.3%
3 8091
 
2.2%
0 5596
 
1.5%
8 5325
 
1.5%
9 5153
 
1.4%
7 4870
 
1.3%
6 4439
 
1.2%
5 3986
 
1.1%

NPCFP44
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
245881 
1
58217 
2
 
15854

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row1
4th row
5th row

Common Values

ValueCountFrequency (%)
245881
76.8%
1 58217
 
18.2%
2 15854
 
5.0%

Length

2024-05-06T23:59:37.872706image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:37.973061image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 58217
78.6%
2 15854
 
21.4%

Most occurring characters

ValueCountFrequency (%)
245881
76.8%
1 58217
 
18.2%
2 15854
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Space Separator 245881
76.8%
Decimal Number 74071
 
23.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 58217
78.6%
2 15854
 
21.4%
Space Separator
ValueCountFrequency (%)
245881
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
245881
76.8%
1 58217
 
18.2%
2 15854
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
245881
76.8%
1 58217
 
18.2%
2 15854
 
5.0%

NPCFP45
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.4 MiB
261735 
1
39128 
2
 
19089

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters319952
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row1
4th row
5th row

Common Values

ValueCountFrequency (%)
261735
81.8%
1 39128
 
12.2%
2 19089
 
6.0%

Length

2024-05-06T23:59:38.080851image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-06T23:59:38.183888image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
1 39128
67.2%
2 19089
32.8%

Most occurring characters

ValueCountFrequency (%)
261735
81.8%
1 39128
 
12.2%
2 19089
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Space Separator 261735
81.8%
Decimal Number 58217
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 39128
67.2%
2 19089
32.8%
Space Separator
ValueCountFrequency (%)
261735
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 319952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
261735
81.8%
1 39128
 
12.2%
2 19089
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 319952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
261735
81.8%
1 39128
 
12.2%
2 19089
 
6.0%

FEX_C
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size2.4 MiB

Interactions

2024-05-06T23:58:56.241929image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:52.183222image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:52.996938image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:53.941924image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:54.700106image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:55.458296image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:56.371006image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:52.332340image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:53.291041image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:54.073850image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:54.833079image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:55.589073image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:56.487826image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:52.457552image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:53.411152image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:54.190617image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:54.960060image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:55.716435image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:56.601774image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:52.586779image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:53.554500image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:54.306014image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:55.079852image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:55.837692image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:56.724232image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:52.731308image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:53.685788image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:54.449069image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:55.210865image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:55.972749image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:56.858262image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:52.870235image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:53.817216image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:54.575513image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:55.334652image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-05-06T23:58:56.111467image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Missing values

2024-05-06T23:58:58.045227image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-06T23:59:01.366025image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

DIRECTORIO_PERDIRECTORIO_HOGDIRECTORIOSECUENCIA_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_C
01010001110100011010001111122230121122222122222232122222222200002222222216,604442041
110100012101000110100012111800002352601135000131111222222222212121110121190001190002211900021900022432221211312216,604442041
21010001310100011010001311123526012112222222222222122125002222202222222121116,604442041
3101001111010011101001111212100001342801112222222222222122221100002225000214000012212226,046357048
410100112101001110100112121222401212222222222222122102222201150000212122221312326,046357048
510100113101001110100113121241240150003112222222222221010122222222022412112221226,046357048
61010011410100111010011412123429011122222222222221222102102202226,046357048
7101002111010021101002111111020002222012112222222222212122129001290022129002290022121112113,840826089
81010021210100211010021211167000221101140000121122222222222221221290021290021290022900222212213,840826089
9101003111010031101003111112140001222512111122222222222121221290022222016700021211217,0111108805
DIRECTORIO_PERDIRECTORIO_HOGDIRECTORIOSECUENCIA_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_C
3199423178351331783513178351313222601211222222222222212222222202243222221
319943317835143178351317835141112226012112222222222222122125002222250002222222121
319944317844113178441317844112512122222222222221222222220224222221
31994531784412317844131784412251212222222222222122222222022422222221
319946317859113178591317859111313521201312222222222222122222222013000002422111221
3199473178741131787413178741111167000221601211222222222222212222112000222022432222111
31994831788111317881131788111132229012122222222222221222222220224322221
3199493178811231788113178811213222901212222222222222122222222022412221211
319950317885113178851317885111322290121222222222222212222222202242221211
31995131788512317885131788512132229012122222222222221222222220224222222221